With few exceptions, the courses listed here take place on the IST Austria campus in Klosterneuburg, Austria, and do not accommodate remote participation or distance/elearning.
Overview tables and schedules can be found here.
For past courses (including spring 2017) please refer to our course archive.
Fall 2017/2018
Biology
Developmental Biology
Anna Kicheva, CarlPhilipp Heisenberg
The course will present and discuss key principles of animal development. We will look at how the specification and spatial organization of diverse cell types is related to shaping, mechanics and growth of developing organs. We will pay special attention to the latest advances in developmental biology and the current important questions in the field. Drosophila, zebrafish, chick, and mouse model systems, as well as embryonic stem cells will be covered. The course will include practical sessions in which the students will get handson experience with some of the model systems presented in the course. General background in biology is highly recommended, prior knowledge of developmental biology is not required.
Course type  Advanced 
Track segment(s)  BIODEV 
Target audience  Biology track students 
Prerequisites  General background in biology is highly recommended, prior knowledge of developmental biology is not required. 
ECTS credits  3 
Evaluation  Participation in class discussions, final presentation 
Starts on  Mon, 27Nov2017 (10:15  11:30), Mondi 3 
Ends on  Wed, 24Jan2018 (10:15  11:30), Mondi 3 
Minimum attendance  4 
Withdrawal deadline  18Dec2017 
Course website  View 
Biology
Introduction to Evolutionary Biology
Beatriz Vicoso, Sylvia Cremer
> COURSE CANCELLED
We will cover aspects of evolutionary biology, with a focus on evolutionary ecology and genomics. Each week, there will be an introductory lecture, followed by a paper discussion.
 Adaptive and nonadaptive evolution (BV):
 Deleterious and beneficial mutations
 Origin of new genes and functions
 Evolution of noncoding sequences (BV):
 Genome size evolution and complexity
 Transposable elements and noncoding RNAs
 Speciation (BV)
 Evolution of sociality and cooperation (SC)
 Sexual selection and the evolution of dimorphic traits (SC)
 Host parasite interactions and symbioses (SC)
Course type  Introductory 
Track segment(s)  BIOEVO 
Target audience  The course is primarily aimed at students with a molecular biology background who are interested in molecular and organismal evolution, but students from other fields are welcome. 
Teaching format  Each week, there will be an introductory lecture, followed by a paper discussion. 
ECTS credits  3 
Evaluation  Every week, students will write a short essay on a selected paper. Each student will also present an article to the rest of the class once during the course. 
Minimum attendance  4 credits students 
Withdrawal deadline  30Oct2017 
Course website  View 
Data Science and Scientific Computing
Deep Learning with Tensorflow
Christoph Lampert
Recent years have seen a revival of artificial neural networks for machine learning and data analysis under the name of “Deep Learning”. Tensorflow is one of the leading programming environments for deep learning models. The course will start by giving an introduction into the current state of deep learning. Afterwards, participants will introduce different models in seminarlike talks. A large part of the course will be handson homework, where participants implement the described models and apply them to real data.
*Please note*: A premeeting will be held on Tuesday, November 14th (1:152:15pm, Mondi 2). If you are considering to participate in this course you are strongly encouraged to attend the premeeting as well, where prerequisites and course format will be discussed. You will also have opportunity to ask any preliminary questions you might have.
Course type  Advanced 
Track segment(s)  CSAI, CSNUM, DSSCPROB, DSSCNUM, DSSCANA, DSSCOPT 
Prerequisites  Participants must be fluent in programming python (alternative programming languages will not be possible). Prior knowledge of deep learning or tensorflow is not required. 
Teaching format  mix of lectures,seminar and practical 
ECTS credits  3 
Reading 

Starts on  Tue, 28Nov2017 (13:15  14:30), Seminar room Big Ground floor / Lab Bldg West 
Ends on  Thu, 25Jan2018 (13:15  14:30), Mondi 2 
Minimum attendance  credit students: 3 
Maximum attendance  credit students: 10 
Withdrawal deadline  19Dec2017 
Course website  View 
Mathematics
Stochastic Homogenization
Julian Fischer
Materials that feature heterogeneities on a microscopic scale – for example, heterogeneous heat
conductivity or heterogeneous elastic moduli – often behave like a homogeneous material on large
scales. At a mathematical level, this corresponds to the observation that solutions to PDEs with
heterogeneous coefficient fields on small scales can often be approximated by solutions to an
effective PDE with constant coefficients. This effect is known as homogenization and has been the
subject of intensive mathematical research in the last decades. However, the main focus of the
mathematical community has been on the setting of materials with perfectly periodic microstructure
(that is, PDEs with periodic coefficients). Unfortunately, real materials are almost never perfectly
periodic. Rather, they typically feature randomly distributed heterogeneities, the correlations of
which decay on scales larger than the microscopic scale. Quantifying the deviation of the behavior of
a material with such random heterogeneities from the behavior of an ideal homogeneous material
(that is, quantifying the deviation of the behavior of PDEs with random coefficient fields from the
behavior of a constantcoefficient effective PDE) is the subject of the theory of quantitative
stochastic homogenization.
In recent years, the quantitative theory of stochastic homogenization has seen a series of
breakthroughs, resulting in the derivation of optimal estimates on homogenization rates. The goal of
this course will be to provide an exposition of the results and the mathematical methods in
stochastic homogenization, including
 Analytical Properties of the Homogenization Corrector and Homogenization Rates
 Structure of Correlations in Stochastic Homogenization
 Regularity Theory for Elliptic Operators with Random Coefficients
 Sensitivity Estimates and Logarithmic Sobolev Inequalities for Ensembles
Course type  Advanced 
Track segment(s)  MATANA, MATPROB 
Prerequisites 

Teaching format  lectures 
ECTS credits  3 
Evaluation  regular assignments 
Starts on  Tue, 28Nov2017 (14:45  16:00), Mondi 3 
Ends on  Thu, 25Jan2018 (14:45  16:00), Mondi 3 
Withdrawal deadline  19Dec2017 
Course website  View 
Mathematics
Maths for quantitative life scientists: Linear Algebra
Peter Franek, Uli Wagner
This course is an introduction to Linear Algebra, aimed primarily at Ph.D. students in the life sciences.
The goal of the course is to develop a solid understanding of fundamental ideas and and techniques
of Linear Algebra, with a particular emphasis on the intuition behind these concepts and the ability to
work with them. This will also prepare students for more advanced courses, e.g., the Data Science and
Scientific Computing Track Core Course.
Topics we will cover include: systems of linear equations, vectors, matrices, vector spaces and linear
functions, inner products and orthogonality, eigenvalues and eigenvectors, and singular value decomposition.
Course type  Introductory 
Track segment(s)  BIOQUANT; NEUQUANT 
Target audience  PhD students in the life scientists with an interest in quantitative methods. 
Teaching format  Lectures and recitations, weekly exercise sheets. 
ECTS credits  3 
Evaluation  Students will be graded based on their performance at the exercise sheets. 
Starts on  Tue, 10Oct2017 (14:45  16:00), Mondi 3 
Ends on  Thu, 23Nov2017 (13:15  14:30), Mondi 3 
Withdrawal deadline  31Oct2017 
Course website  View 
Mathematics
Maths for quantitative life scientists: Probability and Statistical Inference
Jan Maas
The course gives an introduction to probability and statistics aimed at PhD students in the life sciences. The goal is to develop a solid understanding of statistical tools and methods, their range of applicability, and their limitations. Theory and examples will be taught in parallel using the software environment R. We will cover basic notions of probability theory, as well as methods from frequentist and Bayesian statistics.
Course type  Introductory 
Track segment(s)  BIOQUANT; NEUQUANT 
Target audience  PhD students in the life scientists with an interest in quantitative methods. 
Prerequisites  Familiarity with basic calculus is expected. Prior knowledge of probability or statistics is helpful but not required. Students who are not familiar with the basics of "R" are encouraged to attend the intensive course "Introduction to R" taking place in late October/early November 2017. 
Teaching format  Lectures and exercise sheets. 
ECTS credits  3 
Evaluation  Students will be graded based on their performance at the exercise sheets. 
Starts on  Mon, 27Nov2017 (13:15  14:30), Mondi 2 
Ends on  Wed, 24Jan2018 (13:15  14:30), Mondi 2 
Withdrawal deadline  18Dec2017 
Course website  View 
Mathematics
Random Matrices
László Erdös
Random matrices were first introduced in statistics in the 1920's, but they were made famous by Eugene Wigner's revolutionary vision. He predicted that spectral lines of heavy nuclei can be modelled by the eigenvalues of random symmetric matrices with independent entries (Wigner matrices). In particular, he conjectured that the statistics of energy gaps is given by a universal distribution that is independent of the detailed physical parameters. While the proof of this conjecture for realistic physical models is still beyond reach, it has recently been shown that the gap statistics of Wigner matrices is independent of the distribution of the matrix elements. Students will be introduced to the fascinating world of random matrices and presented with some of the basic tools for their mathematical analysis in this course. No physics background is necessary, but some basic probability theory is useful.
Course type  Advanced 
Track segment(s)  MATANA, MATPROB, PHYMAT 
Target audience  Students with orientation in mathematics, theoretical physics, statistics and computer science. 
Prerequisites  No physics background is necessary. Calculus, linear algebra and some basic familiarity with probability theory is expected. 
Teaching format  Lectures 
ECTS credits  3 
Evaluation  Homework and an oral exam 
Starts on  Tue, 10Oct2017 (10:15  11:30), Mondi 3 
Ends on  Thu, 23Nov2017 (11:15  12:30), Mondi 3 
Withdrawal deadline  31Oct2017 
Course website  View 
Mathematics
Selected Topics in Geometry and Topology
Arseniy Akopyan, Herbert Edelsbrunner
It will be a working seminar, with two meetings a week devoted to topics in discrete geometry and topology. Each participant gives one lecture on a topic she chooses but not directly related to the subject of her research. There will be lectures by the two instructors filling in gaps and covering interesting recent developments in the field.
Course type  Advanced 
Track segment(s)  MAT_GEO 
Target audience  PhD students and postdocs. 
Teaching format  Each participant gives one lecture. 
ECTS credits  3 
Evaluation  The students will be evaluated on the basis of the presentations they give. 
Starts on  Mon, 09Oct2017 (10:15  11:30), Mondi 3 
Ends on  Wed, 22Nov2017 (10:15  11:30), Mondi 3 
Minimum attendance  3 
Withdrawal deadline  30Oct2017 
Course website  View 
Neuroscience
Developmental Neuroscience and Brain Diseases
Gaia Novarino, Simon Hippenmeyer
Developmental Neurobiology and Brain Diseases will provide an introduction into the concepts and principles of the basic cellular, molecular and epigenetic mechanisms controlling the assembly of neural circuits in the developing brain. The course will cover general aspects of neurodevelopment (neurogenesis, axon guidance, topographic map formation, specificity of connectivity, glia, epigenetic modulation etc.); and molecular and cellular principles of neural circuit assembly. Neural circuits will be also discussed in the context of neurodevelopmental disorders and neurological diseases in the mature brain. The course is based on contemporary literature and selected text books.
Course type  Introductory 
Track segment(s)  NEUDEV, NEUMOL, NEUTRAN, BIOCELL, BIOMOL 
Target audience  Students at all levels and with all backgrounds (experimental and theory), students intending to affiliate with any neuroscience laboratory or with a cell biology laboratory are recommended to take this class. 
Teaching format  Lectures with unique content, synthesized from most contemporary literature. Student presentations and plenum discussions during exam weeks. 
ECTS credits  6 
Evaluation  Class attendance and participation, paper presentations, essay (5 pages) about a topic discussed in the course. 
Starts on  Mon, 09Oct2017 (08:45  10:00), Mondi 3 
Ends on  Wed, 24Jan2018 (08:45  10:00), Mondi 3 
Minimum attendance  4 
Withdrawal deadline  30Oct2017 
Course website  View 
Neuroscience
Advanced techniques in LS: Manipulation of gene expression level
Sandra Siegert
This course
 Introduces the fundamental concept of cell types and methods of determining gene expression level in vivo.
 Aims at covering both, the basic concepts and methods of gene manipulation techniques as well as how they are applied to address specific research questions.
 Is divided in a theoretical and a practical part to allow a full spectrum of experimental design using in silico planning, performing the experiment, analyze the obtained data, and discuss the results.
Course type  Advanced 
Track segment(s)  NEUMOL, NEUQUANT, BIOQUANT 
Target audience  The course is for all students, who wish to affiliate in one of the life scientists group and with interest to manipulate gene expression levels in vitro or in vivo. The focus of the course is mostly on the mammalian system; however, students outside of this area are strongly encouraged to attend and adapt their cloning strategies to their systemofinterest. 
Teaching format  The course is divided in a theoretical (interactive lectures and recitations) and a practical part. In the practical part, the group is divided in teams of two. The schedule of the practical will be flexible and will depend on the experimental outcome. 
ECTS credits  3 
Evaluation  The participant is expected:

Starts on  Tue, 28Nov2017 (10:15  11:30), Mondi 3 
Ends on  Thu, 25Jan2018 (11:15  12:30), Mondi 3 
Minimum attendance  4 
Maximum attendance  8 
Withdrawal deadline  19Dec2017 
Course website  View 
Physics
Nonlinear Dynamics and Chaos
Björn Hof, Nazmi Budanur
The course will begin by introducing continuous and discrete time dynamical systems, followed by fundamental concepts such as stability, Poincare sections, bifurcation theory, transition to chaos, and qualitative dynamics. Second half of the class will cover a selection of advanced topics and applications according to the interests of participants. Possible topics are spatiotemporal chaos, transition to turbulence, symmetries and symmetry reduction, operatorbased methods, periodic orbit theory, and quantum chaos.
Course type  Advanced 
Track segment(s)  PHYHYDRO 
Target audience  Physics, math, or engineering students with interest in dynamical systems. 
Prerequisites  Basic knowledge of calculus, ordinary differential equations, and linear algebra is assumed. Familiarity with a numerical computing environment (such as python, Julia, or Matlab/Octave) will be helpful. 
Teaching format  2 lectures + 1 recitation a week. 
ECTS credits  6 
Evaluation  Homework assignments and term project. 
Starts on  Tue, 10Oct2017 (10:15  11:30), Mondi 1 
Ends on  Thu, 25Jan2018 (11:15  12:30), Seminar room Ground floor / Lab Bldg West 
Minimum attendance  3 
Maximum attendance  30 
Withdrawal deadline  31Oct2017 
Course website  View 
Physics
Methods of Data Analysis
Gasper Tkacik
This course introduces a variety of data analysis and simulation methods. It is organized around weeklong modules, each covering one method and consisting of 2 lectures, a recitation, and an extensive problem set. The aim is for the students to both understand the method and try it out on real or simulated data. This is a handson course that should provide useful practical experience. The students may find the background of DSSC Track Core course helpful, but it is not required.
Tentative topics to be covered:
 Random numbers, Gillespie (SSA) simulation.
 Monte Carlo and entropic sampling.
 Working with probability distributions, entropy and KLdivergence, density estimation, maximum entropy models.
 Probabilistic models, maximum likelihood / MAP inference.
 Basics of information theory, linear vs information theoretic measures of dependency, redundancy, multiinformation.
 Gaussian processes.
Course type  Advanced 
Track segment(s)  DSSCANA, PHYBIO 
Target audience  Primarily DSSC students but open to any student with: (i) sufficient math background (linear algebra, basic calculus; typically at the level of intro Physics/CS/Engineering/Math undergrads); (ii) sufficient coding capability (working knowledge of a language that supports numerical computation, e.g., Matlab, Mathematica, C, Python, etc). 
Teaching format  Blackboard lectures with some examples and literature reading, recitations to help with the homeworks. 
ECTS credits  3 
Evaluation  100% problem set (homework) assignments 
Starts on  Mon, 09Oct2017 (10:15  11:30), Mondi 2 
Ends on  Wed, 22Nov2017 (10:15  11:30), Mondi 2 
Minimum attendance  3 
Withdrawal deadline  30Oct2017 
Course website  View 
Physics
Modern Atomic, Molecular, and Optical Physics I
Mikhail Lemeshko
In this course, we will survey recent theoretical and experimental developments in the field of Atomic, Molecular, and Optical (AMO) physics. The covered topics include (but are not limited to) manipulation of atoms, molecules, and interactions between them with electromagnetic fields; lasercooling, trapping, and deceleration of atoms and molecules; BoseEinstein condensation and other phenomena in ultracold quantum gases. After introducing the fundamentals, we will discuss the emergent applications to quantum simulation, precision measurements, and chemical physics.
The main concepts of quantum mechanics, quantum optics, and spectroscopy will be presented at a depth depending on the needs of the students.
The course ‘Modern atomic, molecular, and optical physics’ is split in two parts, of which this is the first one. Part I is prerequisite for part II, but students can choose to attend only part I.
Course type  Advanced 
Track segment(s)  PHYAMO 
Target audience  IST PhD students, postdocs, and faculty interested in AMO physics. 
Teaching format  lectures. 
ECTS credits  3 
Evaluation  homework and participation. 
Starts on  Mon, 27Nov2017 (13:15  14:30), Seminar room Big Ground floor / Lab Bldg West 
Ends on  Wed, 24Jan2018 (13:15  14:30), Seminar room Big Ground floor / Lab Bldg West 
Minimum attendance  4 
Withdrawal deadline  18Dec2017 
Course website  View 
Physics
The Physics Of Quantum Dots: From Basic Research To Quantum Bits
Georgios Katsaros
In this course the physics of “artificial atoms” will be presented. Starting from a classical transistor it will be shown how nanoscale transistors exhibit quantum behavior at low temperatures. The physics of spin qubits in single and double quantum dots will be discussed. Latest ideas of how to couple quantum bits will be presented and recent experiments will be discussed. Finally in the second part of the lecture the physics of hybrid superconductingsemiconducting devices will be adressed. Such devices might lead to the socalled Majorana Fermions.
Course type  Advanced 
Track segment(s)  PHYCON 
Prerequisites  Prior knowledge of basic electronics, semiconductor physics and quantum mechanics would be of advantage. 
Teaching format  Lectures. During the recitation a paper related to the subject of the course will be discussed. 
ECTS credits  6 
Evaluation  Oral scientific presentation of a recent paper related to the course subject. The paper will be chosen by the instructors. 
Starts on  Mon, 09Oct2017 (08:45  10:00), Seminar room Big Ground floor / Lab Bldg West 
Ends on  Wed, 24Jan2018 (08:45  10:00), Seminar room Big Ground floor / Lab Bldg West 
Minimum attendance  3 
Withdrawal deadline  30Oct2017 
Course website  View 
Interdisciplinary
Introduction to Research at IST Austria
This course gives an introduction to the research of the IST faculty and is required of all new PhD students. The intent is to foster the interdisciplinary spirit at IST Austria, provide students with a scientific overview to aid them in choosing labs for rotations, and to help students in choosing a doctoral advisor.
Research groups present their work in a 3day symposium.
Course type  Required 
Track segment(s)  n.a. 
Target audience  All IST Austria firstyear PhD students (required course). 
Course website  View 
Interdisciplinary
IST core course
Gaia Novarino, Nick Barton
The IST core course is intended as the ISTScholar PhD program’s signature interdisciplinary course. The course is intended to promote communication between fields, and to teach an understanding of how to model data. The core course aims to do the following:
 Teach topics that are interdisciplinary in nature and that bridge a number of divergent fields of study.
 Teach the diverse language and terminology used in different fields that approach common scientific and mathematical problems.
 Promote the exchange of knowledge and skills between students from divergent backgrounds through active group teaching.
 Promote the development of a student cohort that spans divergent fields.
In this year’s core course, students will work in interdisciplinary groups to tackle a problem related to Gaia’s research, namely, how to make sense of the heterogeneous genetic causes of autism spectrum disorders. The course will bring together elements of molecular biology, neuroscience, and bioinformatics, as well as topics in computer / data science. It will leverage the students’ different strengths to tackle an openended question. Along the way, groups will receive feedback from faculty and discussion leaders. The culmination of the course will be a paper writeup and defense of the group project.
Course type  Required 
Track segment(s)  n.a. 
Target audience  All IST Austria firstyear PhD students (required course). 
Teaching format  Lectures, group work 
ECTS credits  6 
Evaluation  Regular assignments and final project. 
Starts on  Tue, 10Oct2017 (08:45  10:00), Mondi 2 
Ends on  Thu, 25Jan2018 (08:45  10:00), Mondi 2 
Withdrawal deadline  31Oct2017 
Course website  View 
Other
Introduction to Biology
Nick Barton
This session will give a historical overview of biology, explaining the development of both molecular and evolutionary biology. The aim is to summarise the key principles, to introduce basic terminology, and to explain the major questions in current research. No previous knowledge of biology will be assumed.
Further reading:
 Judson, H.F. (1996) The Eighth Day of Creation Cold Spring Harbour Press.
A detailed history of the origins of molecular biology, based on interviews with the key scientists. Long, but very well written, and accessible to nonbiologists.  Barton et al. (2007) Evolution Chs. 1, 2 Cold Spring Harbour Press.
This gives a brief summary of evolutionary and molecular biology, and its development in the mid20th century.
Course type  General 
Track segment(s)  n.a. 
Target audience  Students with little or no prior knowledge of biology 
Teaching format  23 pairs of sessions; one session will be a lecture (~1.25 hours), followed by student presentations and discussion (~2.5 hours) 
Evaluation  Short essay and presentation; no exam. 
Starts on  Mon, 25Sep2017 (14:00  16:00), Mondi 3 
Ends on  Thu, 12Oct2017 (13:00  15:00), Mondi 1 
Withdrawal deadline  27Sep2017 
Course website  View 
Other
Introduction to Programming with Python
Georg Osang
This course provides an elementary introduction to programming with applications in science. The language of choice is Python as one of the most popular programming languages (both in and outside of academia), though many concepts also translate to other programming languages. The main topics include the general concepts of programming (variables, expressions, types, control structures, I/O) and usage of a few scientific toolboxes , such as numpy and matplotlib for data processing and visualization. More advanced exercises will be posed in the scientific context, such as data analysis, data visualization or stochastic simulations.
Course type  General 
Track segment(s)  n.a. 
Target audience  If you are comfortable with nested loops, or recursive functions, you are likely too advanced for the course. In case of doubt, discuss your situation with the instructor. In any case, however, you are welcome to attend as an auditor to learn the syntax and some peculiarities of Python. 
Prerequisites  The course is targeted towards students with little or no prior programming experiences, so there are no prerequisites for taking this course. 
Teaching format  The course consists of 6 handson sessions, most of which last for 3 hours with breaks when needed. The last of these sessions will be more openended and allow for discussing any further open questions. The sessions will consist of brief introductions of concepts followed by inclass exercises to practice these concepts. More exercises will be expected to be completed individually at home, and submitted before the next session, which will begin with explanations and comments on the homework. Some of the homework exercises will be obligatory (because further sessions will depend on understanding them), some will be more openended, so that students can optimize their time with respect to the skills they deem most useful. There will be no further obligatory homework after the last session. 
Evaluation  Final grade (fail/pass) will based on completion of homework exercises. 
Starts on  Mon, 25Sep2017 (09:00  12:00), Mondi 3 
Ends on  Fri, 13Oct2017 (09:00  10:15), Mondi 3 
Minimum attendance  3 
Withdrawal deadline  26Sep2017 
Course website  View 
Other
Introduction to Mathematica
Nick Barton
This short course will give a basic introduction to Mathematica. This is a highlevel language that is perhaps best known for symbolic computation, but which includes a comprehensive range of numerical, graphical and statistical resources. (see www.wolfram.com) IST Austria has a site licence that allows unlimited use, including on the cluster.
The course will give an overview of what is available within Mathematica, and how to get started with the system. Programming in Mathematica is quite different from traditional languages, and is arguably more powerful, especially for exploratory analysis.
Course type  General 
Track segment(s)  n.a. 
Prerequisites  No previous experience is assumed. Mathematica may be appropriate for a wide range of uses: symbolic algebra, numerical computation, data exploration, statistical analysis, etc. 
Teaching format  (Brief) lecture plus example class. 
Evaluation  Attendance and completion of problem sets in class. 
Starts on  Tue, 03Oct2017 (09:00  12:00), Mondi 3 
Ends on  Fri, 13Oct2017 (13:00  16:00), Mondi 3 
Minimum attendance  4 
Withdrawal deadline  04Oct2017 
Course website  View 
Other
A (very) basic introduction to R
Giovanni Zanco
This course provides a very elementary introduction to programming using R, as one of the most widespread programming languages for statistics and data analysis in science.
The course will present the following basic notions:
 Data types
 Data structures
 Operations with data
 packages
 Importing data
 Graphics
 functions
The course consists of 3 2hours sessions and 3 3hours sessions (5 hours per week, 3 weeks). The sessions will be a mix of lecturing and handson exercises. Additional exercises will be given as homework; part of the 3hours sessions will be used to explain solutions to exercises and to answer students' questions.
Software
Students attending the course are required to have R installed on their computers; all sessions will be done working on the software, therefore students should bring their own laptops . R is available for computers operating Linux, OS and Windows, and can be downloaded here.
R can be executed and used via command line; however there exist nice software that provides graphical interface and some easy control on editing and workflow. An example is RStudio, which can be downloaded here. Such software is not required for the course but can be useful to those who are not used to programming and working with the command line.
Students should contact the instructor before the beginning of the course should they have any problem with installing or executing the software.
Course type  General 
Track segment(s)  n.a. 
Target audience  This course offers a very basic introduction to programming with R. It is relevant for students without previous knowledge in R who are planning to attend the Probability course (Maas, Fall 2) or any other courses that require programming experience (e.g. DSSC track core course) If you are in doubt whether this course is appropriate for you, please get in touch with the course instructor directly. 
Prerequisites  There are no prerequisites for this course. There is no final exam but there will be a final exercise sheet to be completed after the end of the lectures. 
Course schedule  Session 1: Wednesday, October 25, 1:303:30 (lecture) Session 2: Friday, October 27, 12:453:45 (exercise) Session 3: Monday, October 30 1:303:30 (lecture) Session 4: Friday, Nov 3, 12:453:45 (exercise) Session 5: Wednesday, Nov 8, 1:303:30 (lecture) Session 6: Friday, Nov 10, 12:453:45 (exercise) 
Starts on  Wed, 25Oct2017 (13:30  15:30), Mondi 2 
Ends on  Fri, 10Nov2017 (12:45  15:45), Mondi 2 
Course website  View 
Other
Mathematics Refresher
Jirí Friml
This lecture course aims to refresh the understanding of basic concepts of mathematics and their applications to give students an introduction to more advanced mathematical challenges waiting in other courses. It will be explained by a nonspecialist in simple terms and an interactive way. It will focus on intuitive rather than formal understanding of basic concepts and will introduce terminology and give a bit of historical perspective.
The course will encompass: arithmetic and algebra; functions and limits; introduction to calculus; initial insights into linear algebra, probability and statistics. In the final lecture, the practical applications of the covered concepts will be reviewed with an initial glimpse into differential equations. The content will not go beyond advanced highschool level and thus is meant mainly for those who have been successfully avoiding exposure to mathematics so far.
Course type  General 
Track segment(s)  n.a. 
Target audience  The content will not go beyond advanced highschool level and thus is meant mainly for those who have been successfully avoiding exposure to mathematics so far. 
Course schedule 

Starts on  Thu, 21Sep2017 (15:00  17:00), Mondi 2 
Ends on  Thu, 05Oct2017 (13:00  15:00), Mondi 3 
Withdrawal deadline  22Sep2017 
Course website  View 
Other
IST Entrepreneurship Lab
Alexander Fischl, Astrid Woollard, Markus Wanko
From sciencebased ARM to tech startup Zalando, they all started with an ambitious idea that later made highly successful businesses. Join us at the IST Entrepreneurship lab, where you can explore your own ideas and learn the basics of commercializing research findings and starting up a business.
This course is open to the IST community; participants are encouraged to think about and develop a specific idea, but we also welcome participants who are still in the search phase.
Course type  General 
Prerequisites  none. 
Teaching format  Lectures, project work. 
Evaluation  Attendance (min 6 out of 8). 
Starts on  Mon, 23Oct2017 (14:30  16:00), Mondi 3 
Ends on  Mon, 11Dec2017 (14:30  16:00), Mondi 3 
Minimum attendance  6 
Maximum attendance  8 
Course website  View 
Other
Introduction to Animal Handling  Fish
Matthias Nowak, Michael Schunn
This course contains the following two modules of the "Introduction to Animal Handling":
1) Ethics, Legislation and Animal welfare (5h theory and discussion);
2) Handling and Experimentation in Fish (4h theory and 4h practical).
Students will be taught relevant theory related to the biology of the species and to the procedural techniques that will be executed during the course. The practical components will take place after the theory is attested by an exam. The goal of the practical component of the course is to allow the participants to acquire the handling skills and feel confident when manipulating animals and executing procedures. Each group of students will be closely supervised by a teacher that will demonstrate and assist the students with all the techniques.
Course type  General 
Track segment(s)  n.a. 
Target audience  all PhD students, postdocs and scientists who stay longer than three months at IST Austria and need to work with laboratory rodents and/or fish 
Evaluation 

Course schedule  September 26: 8:45am4:00pm (Big Seminar Room LBW) September 28: 8:45am4:00pm (Mondi 1) September 29: 8:45am4:00pm (lab; exact venue will be announced) 
Starts on  Thu, 28Sep2017 (08:45  16:00), Mondi 1 
Ends on  Thu, 28Sep2017 (08:45  16:00), Mondi 1 
Withdrawal deadline  27Sep2017 
Course website  View 
Other
Introduction to Animal Handling  Rodents
Joana De Assuncao Almeida, Michael Schunn
This course contains the following two modules of the "Introduction to Animal Handling":
1) Ethics, Legislation and Animal welfare (5h theory and discussion)
2) Handling and Experimentation in Rodents (4h theory and 8h practical)
Students will be taught relevant theory related to the biology of the species and to the procedural techniques that will be executed during the course. The practical components will take place after the theory is attested by an exam. The goal of the practical component of the course is to allow the participants to acquire the handling skills and feel confident when manipulating animals and executing procedures. Each group of students will be closely supervised by a teacher that will demonstrate and assist the students with all the techniques.
Course type  General 
Track segment(s)  n.a. 
Target audience  all PhD students, postdocs and scientists who stay longer than three months at IST Austria and need to work with laboratory rodents and/or fish 
Course schedule  September 26: 8:45am4:00pm (Big Seminar Room LBW) September 28: 8:45am4:00pm (Mondi 2) September 29: 8:45am4:00pm (lab; exact venue will be announced) 
Starts on  Tue, 26Sep2017 (08:45  16:00), Seminar room Big Ground floor / Lab Bldg West 
Ends on  Thu, 28Sep2017 (08:45  16:00), Mondi 2 
Withdrawal deadline  27Sep2017 
Course website  View 
Spring 2018
Biology
Cell Migration
Daria Siekhaus, Michael Sixt
Students will learn about eukaryotic cell biology with a focus on mechanisms of cell migration through lectures and dissection of the
primary literature, both classic papers and ones highlighting recent concepts and technologies. Topics included will be the cytoskeleton, cell signaling, polarity determination, gradient interpretation and cell migration in in vitro and in vivo contexts.
Quantitative and interdisciplinary perspectives on the topics will be highlighted.
Students will further develop their independent thinking, knowledge of the techniques utilized in these areas, ability to critically assess the literature, and presentation skills.
Course type  Advanced 
Track segment(s)  BIOCELL 
Target audience  This course is classified as an advanced course appropriate for biology students interested in learning more about cell migration but is open to students with limited previous knowledge in the field as well. We have selected many papers in which students with advanced knowledge of math will have an advantage. We will adapt the teaching and content according to the students and their background and pair non biology students with biology students for the presentations. Students with limited biology exposure have enjoyed and succeeded in the course in the past. 
Teaching format  Interactive discussion of primary literature. 
ECTS credits  3 
Evaluation  Presentations, participation, mini grant. 
Starts on  Mon, 26Feb2018 (14:45  15:00), Mondi 3 
Ends on  Thu, 26Apr2018 (10:15  11:30), Mondi 3 
Minimum attendance  4 
Maximum attendance  15 
Withdrawal deadline  20Mar2018 
Course website  View 
Biology
Bioinformatics (Genomics and Gene Expression Analysis)
Beatriz Vicoso
We will discuss common types of sequencing data and perform hands on analyses in:
 Genomics:
 DNA sequencing platforms
 Tools for genome assemblies
 Transcriptomics:
 RNAseq and Riboprofiling analysis, detection of differentially expressed genes
 Evolution of gene expression
 Epigenomics:
 Examples of analyses different datasets, including bisulfite sequencing (methylation), DNaseSeq (regulatory regions), ChipSeq (histone modifications).
Course type  Advanced 
Track segment(s)  BIOQUANT, DSQUANT 
Target audience  Experimental biologists and/or theoreticians looking to analyze largescale sequencing data. 
Teaching format  Each week there will be an introductory lecture followed by a computational assignment. 
ECTS credits  3 
Evaluation  Project report. 
Starts on  Tue, 27Feb2018 (13:15  14:30), Mondi 2 
Ends on  Thu, 26Apr2018 (13:15  14:30), Mondi 2 
Minimum attendance  4 credit students 
Maximum attendance  12 
Withdrawal deadline  20Mar2018 
Course website  View 
Biology
Synthetic and Systems Biology I
Anna Kicheva, Calin Guet, Martin Loose
The course covers the history of both fields, which is intertwined. From the earliest papers leading up to present day results will be analyzed and the challenges of the fields will be addressed. Molecular, cellular and multicellular systems will be discussed. The class focuses on the basic science aspects of and not on the more engineering ones.
Course type  Advanced 
Track segment(s)  BIOSYS 
Target audience  Biology track students. 
Prerequisites  General background in biology is highly recommended. 
Teaching format  A combination of lectures and in class discussions. 
ECTS credits  3 
Evaluation  Participation in class discussions, project presentations. 
Starts on  Mon, 26Feb2018 (10:15  11:30), Mondi 3 
Ends on  Wed, 25Apr2018 (10:15  11:30), Mondi 3 
Withdrawal deadline  27Feb2017 
Course website  View 
Biology
Molecular Population Genetics: making sense of sequence data
Beatriz Vicoso, Jitka Polechova, Nick Barton
course description will be provided shortly
Course type  Advanced 
Track segment(s)  BIOEVO, DSSC_QUANT 
ECTS credits  6 
Course schedule  March 5 June 25, 2018: Mondays, 9.0011.30 am 
Venue  University of Vienna, Faculty of Mathematics OskarMorgensternPlatz 1 A1090 Vienna, Austria (details tbd) 
Registration  This course is crosslisted at IST Austria, the University of Vienna, and the Vetmeduni. Please register at your home institution. 
Withdrawal deadline  26Mar2018 
Course website  View 
Biology
Biology track core course
Every big biological problem has a structural, mechanical, evolutionary, genetic and population side to it. The goal of the biology core course is to illustrate that fundamental biological problems and phenomena can be approached from vastly different angles.
In this course we will bridge different areas in biology to show students how fundamental biological problems and phenomena can be approached from different perspectives.
This year we will discuss one broad topic: Spatiotemporal organization. The instructors will provide a list of papers to be studied, typically in the form of a review paper or something equivalent.
Additional instructors  IST biology faculty 
Course type  Track core 
Track segment(s)  BIOCORE 
ECTS credits  6 
Starts on  Mon, 26Feb2018 (08:45  10:00), Mondi 3 
Ends on  Wed, 20Jun2018 (08:45  10:00), Mondi 3 
Withdrawal deadline  19Mar2018 
Course website  View 
Biology
Structural Biology
Leonid Sazanov
Students will learn about advanced topics in Structural Biology through lectures and dissection of the primary literature. Topics included will be the structure and function of proteins and protein complexes, particularly membrane proteins. Methods covered will include Xray crystallography and new cryoEM methods. Quantitative and interdisciplinary perspectives on the topics will be highlighted. Students will further develop their independent thinking, knowledge of the techniques utilized in these areas, and ability to critically assess the literature.
Course type  Advanced 
Track segment(s)  BIOMOL 
Prerequisites  Nonbiologists should read all basic chapters from textbooks below. Biologists should update themselves on the following chapters (books available in IST library):
Structural biology and Xray crystallography basics online: Crystallography 101 The Fourier Picture book and The Interactive Structure Factor Tutorial History 
ECTS credits  3 
Evaluation  30% presentation in class; 25% participation in class; 20% participation in recitations; 25% final essay. Essay: Select a paper in structural biology and write an essay about it in the style of “News and Views” article in Nature, i.e. describe for nonspecialists the significance of the paper. The essay should summarize the main findings of the paper, explain it to a broader audience and discuss its relevance for the field. It should include a Title, Abstract, 1500  2000 words, one figure and references. 
Starts on  Thu, 03May2018 (13:15  14:45), Mondi 1 
Ends on  Thu, 21Jun2018 (13:15  14:45), Mondi 1 
Minimum attendance  4 
Withdrawal deadline  22May2017 
Course website  View 
Computer Science
Formal Methods
Krishnendu Chatterjee
We present formal modeling languages and analysis tools for discreteevent dynamical systems, with applications from computer science. The languages we discuss are based on mathematical logic, automata, and graph game models. The analysis methods include model checking, and graph algorithms. We give brief introductions to advanced models incorporating probabilities, gametheoretic aspects, and continuous behavior.
Course type  Introductory 
Track segment(s)  CSPROG 
Target audience  1st year PhD students 
Prerequisites  Basic mathematical concepts of set theory (union, intersection etc.), and basics of probability. 
ECTS credits  3 
Starts on  Thu, 03May2018 (15:45  17:00), Mondi 1 
Ends on  Thu, 21Jun2018 (15:45  17:00), Mondi 1 
Minimum attendance  5 
Withdrawal deadline  22May2018 
Course website  View 
Computer Science
Computer Science track core course
Krishnendu Chatterjee, Krzysztof Pietrzak, Vladimir Kolmogorov
The goal of the CS core course is to expose students to key ideas in computer science covering randomized algorithms, parametrized algorithms, optimization algorithms, topics in cryptography. The course will cover about six different topics (2 weeks per topic), many of which are centered around either a classical topic or recent research topics.
Course type  Track core 
Track segment(s)  CSCORE 
Target audience  Students planning to affiliate in a computer science research group are encouraged to choose this course as their track core course. 
Prerequisites  A background in basic algorithms is assumed. 
Teaching format  mainly lectures from the instructors. 
ECTS credits  6 
Evaluation  The main grading will be based on homework and some course projects. In some parts a written or oral exam may also be conducted. 
Starts on  Tue, 27Feb2018 (13:15  14:30), Mondi 3 
Ends on  Thu, 21Jun2018 (13:15  14:30), Mondi 3 
Withdrawal deadline  20Mar2017 
Course website  View 
Data Science and Scientific Computing
Applications of Stochastic Processes
Katarina Bodova, Nick Barton
The course will cover basic stochastic processes, emphasizing examples from a range of fields. This will include Markov chains, branching processes, and the diffusion approximation.
Mathematical rigour will be avoided.
Course type  Advanced 
Track segment(s)  DSSCPROB 
Target audience  Students with good mathematical and computational ability, including calculus, probability and matrix algebra. Appropriate for students interested in data science, population genetics, statistical physics, etc. 
Teaching format  Lectures, problems classes 
ECTS credits  3 
Evaluation  Homework (no exam). 
Starts on  Thu, 03May2018 (10:15  11:30), Mondi 1 
Ends on  Thu, 21Jun2018 (10:15  11:30), Mondi 1 
Withdrawal deadline  22May2018 
Course website  View 
Data Science and Scientific Computing
Data Science and Scientific Computing track core course
Bernd Bickel, Christoph Lampert, Gasper Tkacik
Format:
The course is divided into three 4week cycles in which students work in interdisciplinary groups under the supervision of a DSSC faculty member. During each cycle, students first learn the necessary background and tools, and are then coached by faculty to tackle a specific DSSC problem or data set in pairs. Evaluation is based on homeworks and written or oral reports at the end of each cycle.
Topics:
 cycle 1: building and analyzing predictive models (C. Lampert)
 cycle 2: understanding and visualizing data (G. Tkacik)
 cycle 3: numerical simulation of physical systems (B. Bickel)
 Provide handson experience and scientific insight into different DSSC problems and methodologies
 Learn about evaluation criteria for good models in different fields
 Build a community of computational / data students by project work
 Practice the following skills: handling data, extracting knowledge from data, creating models, running numerical simulations, identifying and understanding sources of error, working in mixed background teams, written and oral communication
Course type  Track core 
Track segment(s)  DSSCCORE 
Target audience 

Prerequisites 

Teaching format  classroom lectures and student projects (in small groups) 
ECTS credits  6 
Evaluation 

Starts on  Mon, 26Feb2018 (10:15  11:30), Mondi 2 
Ends on  Wed, 20Jun2018 (10:15  11:30), Mondi 2 
Minimum attendance  4 
Withdrawal deadline  19Mar2018 
Course website  View 
Mathematics
Geometric Representations of Graphs
Radoslav Fulek
Graphs (or networks), are ubiquitous mathematical structures representing pairwise interactions (edges) between objects (the nodes or vertices of the graph). Constructing ``usefull‘‘ geometric representations of graphs is a natural goal arising in many applications and also a way of shedding light on structural properties of graphs. Furthermore, in the recent past we started witnessing that certain high dimensional geometric representations of graphs lead to solutions of otherwise inaccessible combinatorial and algorithmic problems with no apparent relation to geometry.
The aim of the course is to explain to a broad audience popular algorithmic techniques for graph visualization, and demonstrate the usefullness of geometric representations of graphs in algorihmic problems and in characterizing important graph families.
The exact choice of topics will depend on the audience’s background; the possible topics include:
 Rubber band representations of graphs
 Kissing discs representations of graphs
 Colin de Verdière graph invariant
 Orthogonal representations of graphs
 Computing multicomodity flows
Course type  Advanced 
Track segment(s)  MATGEO, MATDISC, CSALG 
Target audience  Students with a solid background in mathematics or theoretical computer science 
Prerequisites  specific prerequisites will be kept minimal, class will be adapted to the background of the audience 
Teaching format  lectures 
ECTS credits  3 
Evaluation  graded homework + class participation + exam 
Starts on  Mon, 30Apr2018 (13:15  14:30), Mondi 3 
Ends on  Wed, 20Jun2018 (13:15  14:30), Mondi 3 
Withdrawal deadline  21May2018 
Course website  View 
Mathematics
Maths for quantitative life scientists: Introduction to Differential Equations
Jack Merrin
This course is intended to introduce the study of dynamical systems represented by ordinary differential equations. Because students have different skill levels, we will spend some time learning how to solve problems using Mathematica.
We will emphasize three ways to understand solutions: analytical, numerical, and qualitative. Some time will be devoted to the basic types of equations you find in a standard differential equations course. We will then focus on some basic problems in biology that use differential equations such as radioactivity/carbon dating, population growth, chemical/enzymatic kinetics, and competition between species.
Course type  Introductory 
ECTS credits  3 
Starts on  Mon, 26Feb2018 (13:15  14:30), Mondi 3 
Ends on  Wed, 25Apr2018 (13:15  14:30), Mondi 3 
Withdrawal deadline  19Mar2018 
Course website  View 
Mathematics
Mathematics track core course
Jan Maas, Uli Wagner
The course provides a glimpse into selected topics of current mathematical research interest. The aim is to familiarize participants with basic notions, problems, and results outside their own research area. The course format emphasizes interaction between students and active engagement.
Course type  Track core 
Track segment(s)  MATCORE 
Target audience  1st year PhD students with a strong mathematical interest. 
Prerequisites  Participants are expected to have a solid mathematical background, at least at the level of a Mathematics BSc. 
Teaching format  Flexible, depending on the number of enrolled students (most likely a mixture of lectures, a reading course, and presentations by the students). 
ECTS credits  3 
Evaluation  Students will be graded based on the quality of the presentations, homework, and active participation in class. Approved 
Starts on  Mon, 30Apr2018 (14:45  16:00), Mondi 2 
Ends on  Wed, 20Jun2018 (14:45  16:00), Mondi 2 
Withdrawal deadline  21May2018 
Course website  View 
Mathematics
Advanced Topics in Analysis
Robert Seiringer
Advanced Topics in Analysis (exact topics to be determined)
Course type  Advanced 
Track segment(s)  PHYMAT, MATANA 
Target audience  Mathematics students 
Teaching format  Lectures 
ECTS credits  3 
Evaluation  homework problems 
Starts on  Tue, 27Feb2018 (10:15  11:30), Mondi 2 
Ends on  Thu, 26Apr2018 (10:15  11:30), Mondi 2 
Withdrawal deadline  20Mar2018 
Course website  View 
Neuroscience
Advanced techniques in LS: Biophotonics/Highresolution fluorescence
Johann Danzl
Fluorescence microscopy has undergone dramatic progress in the past years and constitutes a central tool in the life sciences. The lecture is aimed at biology, neuroscience, and physics students and reflects the interdisciplinary character of modern microscopy. Surpassing the diffraction resolution limit of light microscopy constituted a major breakthrough that was honoured with the Nobel Prize in Chemistry in 2014. In the course, special emphasis will be placed on diffractionunlimited microscopy, aka nanoscopy or superresolution microscopy, like STED, RESOLFT, PALM, STORM. Further stateoftheart optical methods will be discussed that allow the analysis of the activity of cellular ensembles in tissues (including Ca2+ imaging, twophoton imaging, light sheet microscopy and its variants) as well as the strategies to specifically label target structures. The course should not only convey the pertinent concepts but also provide a basis to choose suitable methods and tools in the framework of one's own PhD or postdoctoral research. Likewise it should become clear what the current state of the field is and where these methods need further development. The course will comprise both lecture and mainly interactive sessions, and practical handson sessions on diffractionunlimited microscopy.
Course type  Advanced 
Target audience  The lecture is aimed at students (and postdocs) from the life sciences and physics. There are no specific prerequisites. Care will be taken that the material is accessible both for students with a physics background and those with a life science background. 
Teaching format  Key concepts will be taught in interactive lectures. Students will also be assigned a paper that they should analyze. 
ECTS credits  3 
Evaluation  Evaluation will be based on participation in the course via discussions, paper discussion, and a written report on the practical session. 
Starts on  Tue, 08May2018 (14:45  17:15), Mondi 3 
Ends on  Tue, 19Jun2018 (14:45  17:15), Mondi 3 
Withdrawal deadline  22May2018 
Course website  View 
Neuroscience
Advanced techniques in LS: Virusmediated neuronal tracing and optogenetics
Ryuichi Shigemoto
This course
 Introduces the fundamental concepts of neuronal pathways and methods of tracing and optogenetics in vivo.
 Aims at covering both, the basic concepts and methods of virusmediated neuronal tracing and expression of channelrhodopsin, optogenetic stimulation, and detection of immediate early gene expression, as well as how they are applied to address specific research questions.
 Is divided in a theoretical and a practical part to allow a full spectrum of experimental design using useful websites like Allen Brain Atlas, performing virus injection and optogeneitc stimulation experiment, preparation of brain sections and IEG detection, analysis of the obtained data, and discuss the results.
Course type  Advanced 
Track segment(s)  NEUMOL, NEUQUANT 
Target audience  The course is for all students, who are interested in neuronal tracing and optogenetics. No previous experience in mouse surgery is needed. The focus of the course is mostly on the mammalian system, in particular mice. 
Teaching format  The course is divided in a theoretical (interactive lectures and recitations) and a practical part. In the practical part, the group is divided in teams of two. The schedule of the practical will be flexible and will depend on the experimental outcome. 
ECTS credits  3 
Evaluation  The participant is expected:

Starts on  Tue, 27Feb2018 (10:15  11:30), Seminar Room / Lab Bldg East 
Ends on  Thu, 26Apr2018 (10:15  11:30), Seminar Room / Lab Bldg East 
Minimum attendance  4 
Maximum attendance  6 
Withdrawal deadline  20Mar2018 
Course website  View 
Neuroscience
Neuroscience track core course
Jozsef Csicsvari, Maximilian Jösch, Peter Jonas
The goal of the neuroscience core course is to teach students basic concept of neuroscience and provide them a general overview of the structures, functions and building blocks of the brain  from molecules to systems. Students will experience conceptual ideas behind classic and novel discoveries, and get a general understanding of the essential methodological strategies required for those breakthroughs.
Students will have to present one publication in a Journal Club style presentation. This exercise will (i) test their critical reading and (ii) challenge their interpretation skills. To finalize the course, each student will also have to review a publication in written form to test their critical thinking, methodological knowledge and writing skills. Thus, our course is designed not only to provide a core knowledge in basic neuroscience, but also to foster critical thinking.
Topics for 2017/2018 (order to be determined based on scheduling)
 Module 1: From Molecules to Single Cells. Topic covered: Channels, Electrical properties of neuronal Communication, Synapses, Neurotransmission, Modulation of Synaptic Transmission, Synaptic plasticity and memory, Neurons (types and functions), Pathophysiology. (Jonas)
 Module 2: Neuronal systems from neuronal circuits to behaviour. This will cover sensory systems (Vision, Olfaction, Audition, Touch, Vestibular System) as well as higher visual processing and sensorimotor transformation. It will also discuss brain systems involved in some fundamental brain functions such as sleepwaking cycle regulation and memory formation. (Jösch, Csicsvari)
Course type  Track core 
Track segment(s)  NEUCORE 
Target audience  Students planning to affiliate in a neuroscience research group. 
Prerequisites  No specific background is required. For students with no background in lifesciences certain aspects of the course will require further reading. 
ECTS credits  6 
Evaluation  50% assignements:
50% final exam essay 
Starts on  Tue, 27Feb2018 (08:45  10:00), Mondi 3 
Ends on  Thu, 21Jun2018 (08:45  10:00), Mondi 3 
Withdrawal deadline  20Mar2018 
Course website  View 
Physics
Modern Atomic, Molecular, and Optical Physics II
Mikhail Lemeshko
In this course, we will survey recent theoretical and experimental developments in the field of Atomic, Molecular, and Optical (AMO) physics. The covered topics include (but are not limited to) manipulation of atoms, molecules, and interactions between them with electromagnetic fields; lasercooling, trapping, and deceleration of atoms and molecules; BoseEinstein condensation and other phenomena in ultracold quantum gases. After introducing the fundamentals, we will discuss the emergent applications to quantum simulation, precision measurements, and chemical physics.
The main concepts of quantum mechanics, quantum optics, and spectroscopy will be presented at a depth depending on the needs of the students.
The course ‘Modern atomic, molecular, and optical physics’ is split in two parts, of which this is the second one. Part I (fall 2017) is prerequisite for part II.
Course type  Advanced 
Track segment(s)  PHYAMO 
Target audience  IST PhD students, postdocs, and faculty interested in AMO physics 
Prerequisites  Modern atomic, molecular, and optical physics I 
Teaching format  lectures 
ECTS credits  3 
Evaluation  homework and participation. 
Starts on  Mon, 26Feb2018 (13:15  14:30), Seminar room Big Ground floor / Lab Bldg West 
Ends on  Wed, 25Apr2018 (13:15  14:30), Seminar room Big Ground floor / Lab Bldg West 
Minimum attendance  4 
Withdrawal deadline  19Mar2018 
Course website  View 
Physics
Physics track core course
Georgios Katsaros, Johannes Fink, Maksym Serbyn, Mikhail Lemeshko
The goal of the course is to familiarize the students with methods, concepts and ideas of current interest in physics. The instructors will provide a list of topics to be studied, typically in the form of a review paper or something equivalent. The topics which will be covered will be related to modern trends in theoretical and experimental “quantum related” research. Each student gets assigned a topic which is closest to his/her area of expertise, and for which he/she will act as an “advisor”. Each student also gets assigned a topic which is chosen outside his/her own area of expertise, and which he/she will study during this course, with the help of the “advisor”. There will be weekly meetings with the instructors to discuss the topics and the progress made by the students. During the second half of the course, each student is expected to give a presentation on the specific topic chosen.
Course type  Track core 
Track segment(s)  PHYCORE 
Target audience  1st year PhD students who are considering to affiliate in a Physics group. 
Prerequisites  Participants should have a background in quantum mechanics and condensed matter physics. 
Teaching format  The students will be assigned with review papers which are covering a “complete” research field. The students are expected to extract the most important information contained in the articles and present it to their peers (in the presence of the instructors) in a pedagogical way. The goal of the core course is to provide to the students a good overview of modern research topics. The students are encouraged to meet the instructors in one to one meetings during the semester in order to discuss open questions. 
ECTS credits  3 
Evaluation  The students will be evaluated by their final presentation. A fail/pass system will be applied. 
Starts on  Thu, 03May2018 (10:15  11:30), Mondi 3 
Ends on  Thu, 21Jun2018 (10:15  11:30), Mondi 3 
Withdrawal deadline  22May2018 
Course website  View 
Physics
Condensed Matter Physics
Maksym Serbyn
This class is covering basiclevel to advanced theoretical treatment of theory of solids. The aim is to provide with an indepth background so that student will be able to orient and understand current subject of research interest in the field.
Tentative curriculum:
 Free electrons: crystalline lattices, band structure, topological insulators
 Electrons in magnetic fields: semiclassic equations of motion, magnetooscillations
 Phonons: electronphonon interactions, polaronic physics
 Effect of interactions on electrons: superconductivity, Mott insulators, magnetism
 [if time permits] Effects of disorder; Kubo formula; scaling theory of localization
Course type  Advanced 
Track segment(s)  PHYCON 
Target audience  Intended for students pursuing degree in quantum physics. 
Prerequisites  basic quantum mechanics, second quantization, some exposure to undergraduate solid state physics is preferable but not required. 
Teaching format  blackboard lectures twice a week, in addition recitation/student presentations that will be covering various experimental methods in relation with the course material 
ECTS credits  6 
Evaluation  if there are more than 10 students are enrolled: 50% participation + 25% homework + 25% final exam if enrollment is less than 10 students: 50% participation + 25% homework + 25% inclasspresentation 
Starts on  Tue, 27Feb2018 (08:15  10:00), Mondi 2 
Ends on  Thu, 21Jun2018 (08:15  10:00), Mondi 2 
Minimum attendance  5 
Withdrawal deadline  22May2018 
Course website  View 
Other
Introduction to Matlab
Mantas Gabrielaitis
course description will be provided shortly
Course type  General 
Track segment(s)  n.a. 
Course schedule  This course is planned to take place as a blocked course in the February semester break (Jan 29Feb 23, 2018); details will follow shortly. 
Course website  View 
Fall 2018/2019
Biology
Introduction to Evolutionary Biology
Beatriz Vicoso, Sylvia Cremer
We will cover aspects of evolutionary biology, with a focus on evolutionary ecology and genomics. Each week, there will be an introductory lecture, followed by a paper discussion.
 Adaptive and nonadaptive evolution (BV):
 Deleterious and beneficial mutations
 Origin of new genes and functions
 Evolution of noncoding sequences (BV):
 Genome size evolution and complexity
 Transposable elements and noncoding RNAs
 Speciation (BV)
 Evolution of sociality and cooperation (SC)
 Sexual selection and the evolution of dimorphic traits (SC)
 Host parasite interactions and symbioses (SC)
Please note that this is a preliminary course description. The final version will be available closer to the starting date of the course
Course type  Introductory 
Target audience  The course is primarily aimed at students with a molecular biology background who are interested in molecular and organismal evolution, but students from other fields are welcome. 
ECTS credits  3 
Course schedule  This course most likely will be offered in the first half of the 2018/19 fall semester. 
Biology
Statistics for Life Sciences
Sylvia Cremer
Statistical data analysis is a key component of all experimental work in the life sciences. It is important to develop a concept of later data analysis already before data generation (experimental design, sample size etc.), which is why statistical planning should be an integral part of every experiment. This course aims to give an overview of data structure and statistical analysis tools, from an applied perspective. The course consists of lectures and handsontraining using the freeware statistical program R.
Please note that this is a preliminary course description. The final version will be available closer to the course start date.
Course type  Introductory 
Track segment(s)  BIOQUANT; NEUQUANT 
Target audience  biology or neuroscience students 
ECTS credits  3 
Course schedule  This course most likely will be offered in the second half of the 2018/19 fall semester. 
Neuroscience
Developmental Neuroscience and Brain Diseases
Gaia Novarino, Simon Hippenmeyer
‘Developmental Neurobiology and Brain Diseases’ will provide an introduction into the concepts and principles of the basic cellular, molecular and epigenetic mechanisms controlling the assembly of neural circuits in the developing brain. The course will cover general aspects of neurodevelopment (neurogenesis, axon guidance, topographic map formation, specificity of connectivity, glia, epigenetic modulation etc.); and molecular and cellular principles of neural circuit assembly. Neural circuits will be also discussed in the context of neurodevelopmental disorders and neurological diseases in the mature brain. The course is based on contemporary literature and selected text books.
Please note that this is a preliminary course description. The final version will be available closer to the starting date of the course
Course type  Introductory 
Track segment(s)  NEUDEV, NEUMOL, NEUTRAN, BIOCELL, BIOMOL 
Target audience  Students at all levels and with all backgrounds (experimental and theory), students intending to affiliate with any neuroscience laboratory or with a cell biology laboratory are recommended to take this class. 
ECTS credits  6 
Course schedule  This course most likely will be offered in the 2018/19 fall semester (full semester course). 
Spring 2019
Biology
Classics in Evolutionary Biology I
Nick Barton
As a field, evolutionary biology is remarkably diverse, ranging from taxonomy to theoretical population genetics, and from paleontology through to experimental evolution. In developing the reading curricula the instructors have attempted to both follow the historical development of the field, and to highlight those works that have had an important impact on evolutionary thinking. The ultimate goal of the course is to provide students with an in depth introduction to a variety of topics in evolutionary biology, and encourage independent exploration of the literature. In addition, scientists do not simply perform experiments or derive equations but must present this information to a wider audience through seminars, conference talks, and manuscripts. Therefore, the course also focuses on providing the important experience of giving oral presentations and scientific writing.
Please note that this is a preliminary course description. The final version will be availble closer to the course start date.
Course type  Advanced 
Track segment(s)  BIOEVO 
Prerequisites  Some knowledge of evolutionary biology helpful – for example, from the “Introduction to Evolutionary Biology" (Vicoso/Cremer) 
ECTS credits  3 
Course schedule  This course most likely will be offered in the 1st half of the 2019 spring semester. 
Biology
Synthetic and Systems Biology II
A course description will be available closer to the course start date.
Course type  Advanced 
Track segment(s)  BIOSYS 
ECTS credits  3 
Course schedule  This course most likely will take place in the 1st half of the 2019 spring term. 
Biology
Bioinformatics (Genomics and Gene Expression Analysis)
Beatriz Vicoso
We will discuss common types of sequencing data and perform hands on analyses in:
 Genomics:
 DNA sequencing platforms
 Tools for genome assemblies
 Transcriptomics:
 RNAseq and Riboprofiling analysis, detection of differentially expressed genes
 Evolution of gene expression
 Epigenomics:
 Examples of analyses different datasets, including bisulfite sequencing (methylation), DNaseSeq (regulatory regions), ChipSeq (histone modifications).
Please note that this is a preliminary course description. The final veresion will be available closer to the course start date.
Course type  Advanced 
Track segment(s)  BIOQUANT, DSQUANT 
Target audience  Experimental biologists and/or theoreticians looking to analyze largescale sequencing data. 
ECTS credits  3 
Course schedule  This course most likely will be offered in the 1st half of the 2019 spring semester. 
Biology
Microfluidics
Jack Merrin
This half course will cover microfluidics with a focus on biological applications and how students can incorporate microfluidics in their research. In this course, students will gain an intuitive understanding of the behavior of fluids on the micro scale. We will discuss microfabrication methods as well as common microfluidic platforms such as flow cytometry and inkjet. Then we will discuss biological applications of microfluidics to cell culture, bacteriology, eukaryotic cells, biochemistry, immunology, neuroscience, medicine, diagnostics, chemical and cell surface patterning, 3D printing, and lab on a chip. .
Topics
 Fluid mechanics, consequences of life at low Reynolds number
 Microfabrication of microfluidics devices, microfluidic valve technology
 Application of inkjet, DNA Printer, Gene chips
 Flow cytometry, digital microfluidics
 Microfluidic cell culture
 Microfluidics in microbiology
 Microfluidics with eukaryotic cells
 Microfluidics in immunology
 Microfluidics in neuroscience and biochemistry
 Microfluidics in medicine and diagnostic miniaturization
 Methods of chemical and cell patterning of surfaces
 Lab on a chip, biological 3D printing
Please note that this is a preliminary course description. The final version will be available closer to the course start date.
Course type  Introductory 
Target audience  We will consider primarily biological applications, but the course should be of interest to anyone who is curious about microfluidics. 
Prerequisites  A basic understanding of calculus is useful but not required to succeed in this class. 
ECTS credits  3 
Interdisciplinary
Advanced techniques in LS: Biophotonics/Highresolution fluorescence
Johann Danzl
Fluorescence microscopy has undergone dramatic progress in the past years and constitutes a central tool in the life sciences. The lecture is aimed at biology, neuroscience, and physics students and reflects the interdisciplinary character of modern microscopy. Surpassing the diffraction resolution limit of light microscopy constituted a major breakthrough that was honoured with the Nobel Prize in Chemistry in 2014. In the course, special emphasis will be placed on diffractionunlimited microscopy, aka nanoscopy or superresolution microscopy, like STED, RESOLFT, PALM, STORM. Further stateoftheart optical methods will be discussed that allow the analysis of the activity of cellular ensembles in tissues (including Ca2+ imaging, twophoton imaging, light sheet microscopy and its variants) as well as the strategies to specifically label target structures. The course should not only convey the pertinent concepts but also provide a basis to choose suitable methods and tools in the framework of one's own PhD or postdoctoral research. Likewise it should become clear what the current state of the field is and where these methods need further development. The course will comprise both lecture and mainly interactive sessions, and practical handson sessions on diffractionunlimited microscopy.
Please note that this is a preliminary course description. The final version will be available closer to the course start date.
Course type  Advanced 
Track segment(s)  BIOQUANT, NEUQUANT, PHYBIO 
Prerequisites  There are no specific prerequisites. Care will be taken that the material is accessible both for students with a physics background and those with a life science background. 
ECTS credits  3 
Course schedule  This course most likely will take place in the 2nd half of the 2019 spring semester. Details will be communicated in due course. 
Biology
Plant Cell and Developmental Biology
Eva Benková, Jirí Friml
Plant Cell and Developmental Biology course will offer PhD students core lectures addressing contemporary topics and challenging questions of plant cell and developmental biology. Students will be introduced to the concepts, scientific fundamentals and methodologies central to contemporary plant biology. At the end of the course students should have an understanding of the experimental approaches, and how they are applied to specific problems in cell and developmental biology; should be able to understand and interpret simple experiments in cell and developmental biology. Assessment for this course will be through ability of students to present selected research article, and to prove its understanding in general context during following discussion.
Please note that this is a preliminary course description. The final version will be available closer to the starting date of the course
Course type  Introductory 
Track segment(s)  BIOCELL 
Target audience  Students interested in contemporary molecular and genetic tools and their implementation to address cell and developmental biology questions. 
ECTS credits  3 
Course schedule  This course most likely will be offered in the second half of the 2018/19 fall semester. 