Neural Systems and Computation

The Master's program in Neural Systems and Computation at the University of Zurich is a cutting-edge interdisciplinary program designed for students interested in understanding the fundamental principles underlying neural function and computational processes in biological systems. This program offers a rigorous curricula that combines insights from neuroscience, computer science, physics, and mathematics, providing students with both theoretical knowledge and practical skills necessary for advancing research in neural systems, artificial intelligence, and data analysis. Students will explore the structure and function of neural circuits, learn about neural modeling and simulation techniques, and develop proficiency in analyzing complex neural data. The program emphasizes a hands-on approach through laboratory sessions, project work, and collaborations with leading research institutes. Graduates will be well-equipped to pursue careers in academic research, industry, or healthcare, where they can contribute to innovations in neurotechnology, machine learning, and neuroinformatics. The program also encourages critical thinking about the ethical and societal implications of neural and computational technologies. With access to state-of-the-art facilities and a vibrant academic community, students will engage in frontier research projects, attend specialized seminars, and participate in workshops that foster an environment of innovation and discovery. The Master's in Neural Systems and Computation prepares students to be at the forefront of understanding brain function and developing intelligent systems inspired by biological neural networks. This program is ideal for highly motivated individuals with a background in science, engineering, or mathematics who are eager to explore the complexities of the nervous system and its computational aspects in a collaborative and stimulating academic setting.

The program consists of a set of core modules, elective core modules, a set of elective modules, and a Master’s thesis. Students may choose, in consultation with their mentor, a selection of core and elective courses to suit their backgrounds and goals. The Master’s thesis is mandatory and students have the option to reduce the duration of the thesis project in favor of two short research projects.

The core courses provide a common foundation for students with different educational backgrounds. The set of elective core courses cover the following:

1. Systems Neurosciences
2. Neural Computation and Theoretical Neurosciences
3. Neurotechnologies and Neuromorphic Engineering

Students must attend core courses from at least two of the three above listed disciplines (see Credit Point System).

In addition to theoretical courses, the core modules include a practical education in instrumentation, measurement, and data analysis relevant to neuroinformatics as well as an opportunity to study, discuss, and report on a list of foundational research papers in neuroscience and computation. In addition, a journal club, held with graduate students and INI staff, will provide a forum for the analysis and evaluation of recently published high-profile research. The journal club provides a state-of-art awareness of progress in the field.

The program is affiliated with the Mathematics and Natural Sciences Faculty (MNF) at the University of Zurich (UZH) and theInformation Technology and Electrical Engineering Department (DITET) of the ETH Zurich.

Since 2011, students are awarded a Joint Master Degree UZH/ETHZ. The leading house of this Joint Master is the University of Zurich, regulations are according to guidelines of the University of Zurich.

Core Modules

• Basics of Instrumentation, measurement, and analysis (4 ECTS)
• Readings in Neuroinformatics (3 ECTS)
• Journal Club (2 ECTS)
• Colloquium (0 ECTS)

Elective Core Modules

The Elective Core Courses are divided into three categories, covering the basics of neural computation in experiment, theory, and technology. Students need to obtain a total of 18 ECTS credits from elective core courses with at least 9 ECTS credits from each of two of the three categories listed below. Credit points for each course are obtained after successfully passing an oral or written examination.

Systems Neuroscience

Systems Neuroscience covers the anatomy and physiology of vertebrate brain areas with an emphasis on computational function.

Current courses include:

• Introduction to Neuroinformatics, by Kevan Martin, Matthew Cook, Valerio Mante, Michael Pfeiffer, 6 ECTS credits
• Introduction to Systems Neuroscience, by Daniel Kiper, 6 ECTS credits
• Computational Vision, by Kevan Martin and Daniel Kiper, 6 ECTS credits

Neural Computation and Theoretical Neurosciences

Neural Computation and Theoretical Neurosciences covers state-of-art approaches to understanding the information content of neural signals, and biophysical models of neural systems at the level of single cells and of networks. It also covers aspects of computation in a broader sense based on neuron-like computational primitives.

Current courses include:

• Introduction to Neuroinformatics, by Kevan Martin, Matthew Cook, Valerio Mante, Michael Pfeiffer, 6 ECTS credits
• Neurophysics, by Richard Hahnloser, Jean-Pascal Pfister, 6 ECTS credits (this course will be replaced next year by a new one entitled "Neural Systems", details will follow)
• Methods & Models for fMRI Data Analysis, by Klaas Enno Stephan, 6 ECTS credits (before 2016: 3 ECTS credits)
• Computational Neuroimaging Clinic, by Klaas Enno Stephan, 3 ECTS credits
• Computational Psychiatry, by Klaas Enno Stephan, 3 ECTS credits
• Translational Neuromodeling by Klaas Enno Stephan, 6 ECTS credits (before 2016: 3 ECTS credits)
• Models of Computation, by Matthew Cook, 6 ECTS credits
• Theory, Programming, and Simulation of Neural Networks, by Ruedi Stoop, 6 ECTS credits

Neurotechnologies and Neuromorphic Engineering

Neurotechnologies and Neuromorphic Engineering covers the basics of transistor physics and of electronic circuits mimicking neural sensing and signal processing.

Current courses include:

• Introduction to Neuroinformatics, by Kevan Martin, Matthew Cook, Valerio Mante, Michael Pfeiffer, 6 ECTS credits
• Neuromorphic Engineering I, by Tobi Delbruck, Giacomo Indiveri, and Shih-Chii Liu, 6 ECTS credits
• Neuromorphic Engineering II, by Tobi Delbruck, Giacomo Indiveri, and Shih-Chii Liu, 6 ECTS credits
• Bioelectronics and Biosensors by Janos Vörös, Fatih Yanik, and Tomaso Zambelli, 6 ECTS credits

Elective Modules

Elective modules can be freely selected (with certain restrictions, see below) from the modules offered by the University of Zurich and ETH Zurich. If you are in doubt about whether a course can be accredited, approval from the Masters Program Coordinator (nsc@ini.uzh.ch) must be sought before taking the respective course.

Restrictions for UZH Students

UZH students can (but do not have to) choose 2 of the 18 ECTS credits from any UZH or ETH module under the following restrictions:

• Language courses for English, French, Italian, and Spanish are only accredited from Level B2 (Advanced) onwards. German language courses are only accredited from Level C2 onwards.
• Courses designed to provide basic academic or professional skills cannot be accredited. This means that courses on subjects such as Business English, Presentation Skills, Authoring Academic Papers, Software Programming, Organizing One’s Work, etc., cannot be accredited as an Elective Module.

Suggested Elective Modules

The following is an incomplete list of UZH / ETH courses that may be selected as Elective Modules. Courses in physical, biological, engineering, and computational sciences not listed here may apply as Elective Modules as well. Every course listed under Elective Core Modules is also pre-approved as an Elective Module (but counts only for one category). Students are encouraged to consult with the Masters Program Coordinator (nsc@ini.uzh.ch) about the applicability of individual courses.

Sample Elective Courses (in categories):

Neuroscience and Biology

• 327-0703-00L: Electron Microscopy
• 551-0305-00L: Development of the Nervous System
• 551-0324-00L: Systems Biology
• 227-1047-00: The Neurobiology of Consciousness
• 551-0427-00L: Advanced Course in Neurobiology I
• 701-1418-00: Modeling course in population and evolutionary biology
• 251-0523-00L: Computational Biology
• BIO 343: Structure, plasticity, and repair of the nervous system
• BIO 402: Systems Neurobiology
• BIO 434: Electrophysiological Recording Techniques
• DOEC0133: Decision Neuroscience
• 551-0416-00L: Neurowissenschaften
• 227-0390-00L: Elements of Microscopy
• 376-1428-00L: Comparative Behavioural Neuroscience
• 376-1414-00L: Current Topics in Brain Research

Computational Neuroscience and Artificial Intelligence

• 227-1044-00:    Auditory Informatics
• 402-0588-00L:    Dynamische Systeme in der Biologie I: Mathematische Grundlagen
• 402-0805-00L:    Dynamische Systeme in der Biologie II: Anwendungen
• 252-0535-00: Machine Learning
• 151-0626-00L: Neural Networks
• 263-5210-00L: Probabilistic Artificial Intelligence
• 252-3005-00L: Introduction to Natural Language Processing
• 263-3210-00L: Deep Learning
• 263-5200-00L: Data Mining: Learning from Large Data Sets
• 252-0220-00L: Learning and Intelligent Systems

Electrical Engineering, Signal Processing, and Applications

• 227-0147-00L:    Entwurf von hochintegrierten Schaltungen
• 227-0427-00L:    Signal and Information Processing: Modeling, Filtering, Learning
• 227-0116-00L: VLSI I: From Architectures to VLSI Circuits and FPGAs
• 227-0147-00L: VLSI II: Design of Very Large Scale Integration Circuits
• 227-0148-00L: VLSI III: Test and Fabrication of VLSI Circuits
• 151-0623-00L: Distinguished Seminar in Robotics, Systems, and Controls
• 376-0210-00L: Biomechatronics

Cognitive Science and Neuroeconomics

• DOEC0133: Decision Neuroscience
• MOEC0336: Principles of Neuroeconomics
• BOEC0120: Introduction to Neuroeconomics & Social Neuroscience
• DOEC0444: Non-Invasive Brain Stimulation for Neuroeconomics
• 200x704b: Current Topics in Cognitive Psychology

Clinical Neuroscience and Neurorehabilitation

• 376-1217-00L:    Rehabilitation Engineering I
• 376-1219-00L:    Rehabilitation Engineering II
• 376-1279-ooL:    Virtual Reality in Medicine
• 376-1306-00: Clinical Neuroscience
• 376-0300-00L    Translational Science for Health and Medicine

Computer and Computational Science, Programming

• 402-0981-00:    Computersimulationen sensorischer Systeme
• 402-0811-00:    Programmiertechniken für Physikalische Simulationen
• 251-0540-00L: Computational Science
• ESC 403: Introduction to Data Science
• SPI 301: Computergestütztes Experimentieren I
• SPI 202: Einsatz der Computersimulation in den Naturwissenschaften II
• 851-0144-21L: Philosophical Issues and Problems in Theoretical Computer Science

Mathematical Foundations

• 401-0603-00L:    Stochastik
• 227-1030-00: Complex Systems: Berechenbares Chaos in dynamischen Systemen
• 363-0588-00L: Complex Networks
• 252-0055-00L: Informationstheorie
• 376-1719-00L: Statistics for Experimental Research

Physics

• 402-0809-00L:    Introduction to Computational Physics
• 402-0577-00: Quantum Systems for Information Technology
• 402-0340-BSL: Medizinische Physik
• 402-0341-00L: Medizinische Physik I
• 402-0673-00L: Physics in Medical Research: From Humans to Cells
• 402-0207-00L: Theorie der Wärme

MSc Thesis and Exam

MSc Thesis

The MSc Thesis involves independent research carried out under the guidance of a Professor of the University of Zurich or the ETH Zurich. Under some circumstances, the student may do the MSc Thesis at an external University or Company. External Theses must be pre-approved by the NSC Director or NSC coordinator. The expected work time of a long MSc Thesis is 9 months, and 6 months for a short Thesis. Students choosing to do a short Thesis must complete two additional short research projects (see below).

Students are not required to work full time on their Thesis, but have the freedom to go about other curricular activities during their Thesis work. In this latter case, the Thesis duration increases accordingly (the total work time must sum up to at most 9 or 6 months full time, including the write up).

As soon as a supervisor for the Thesis has been identified, students are requested to fill out the registration (PDF, 81 KB) and have it signed by the one of the NSC Professors (who may be a different person than the supervisor) and must give the original to the Program Administrator.

The MSc Thesis is graded by the Professor, after consultation with the supervisor if applicable. The written and approved report needs to be handed in as a paper version to the Program Administrator, and a PDF version, together with all necessary data needs to be uploaded to a data repository.

Short Project

The Short Project gives the student some hands-on experience with research. A Short Project involves 6 weeks of full-time work, or an equivalent amount of work distributed over a longer time interval. The research projects must be on different topics than the Masters Thesis and different from one another. The Short Project requires also a registration (PDF, 81 KB) to the Program Administrator. The pass/no pass decision of a Short Project is made by the Project Supervisor and is based on a written report. The written and approved report needs to be handed in as a paper version to the Program Administrator, and a PDF version, together with all necessary data needs to be uploaded to a data repository.

MSc Examination

The MSc examination is an oral examination, and is the last exam of your MSc.

The MSc Thesis, Short Projects and courses must be completed and handed in before the oral examination can take place. Your supervisor needs to check that all data necessary has been uploaded to a data repository. In addition the program administrator needs to be provided with a paper print of your MSc Thesis and Short Projects. MSc Thesis and Short Projects need to be dated and signed by the supervisor.

The duration of the oral exam is half an hour. During 20 minutes the student presents a concise summary of his/her Thesis Work to the Supervisor (if possible) and the Professor. The oral exam usually takes place during the weekly Institute meeting (the ‘lab’ meeting). A slot in the weekly Institute meetings must be scheduled with Prof. Giacomo Indiveri and communicated to the Program Administrator.

Make sure you pick a date when your Supervisor(s) can be present.

The oral exam and thesis are graded by the Supervisor, and the co-examiner if applicable. The final grade of the MSc Examination is weighted as follows:

Long Thesis: final grade= 0.82*(grade Thesis)+0.18*(grade oral exam)

Short Thesis: final grade= 0.72*(grade Thesis)+0.28*(grade oral exam)

(1) Supply an electronic version of the following documents to nsc@ini.uzh.ch. Your application must be in English, and all your documents must be combined into max. 1 – 2 PDF-files:

• Completed application form (DOC (DOC, 48 KB) or PDF (PDF, 104 KB))
• Curriculum vitae (resume)
• A max. one-page motivation letter stating the reasons for your interest in this program
• Full details about your Bachelor’s degree including the complete transcript of academic records
• For non Swiss citizens: A short financial statement describing how you plan to cover your living expenses in Switzerland while enrolled in the program (no bank details needed)

In your application form you are required to provide the following information:

• Names of the preferred and second-preferred mentor from the list below (the role of the mentor is to help you plan a personal curriculum; you do not need to contact the mentors before submitting your application)
• Two reference contacts; name, position, phone, e-mail (no letters needed)

(2)  The evaluation process will take about 1-2 months, starting with the respective application deadline (15 January or 15 August). As soon as you will have received a positive recommendation for the University Zurich, the UZH admission office will get in touch with you for the formal part. Please note that the UZH admission office will ask you again for most of the documents.

Choose a preferred and a second-preferred mentor from the list below (the role of the mentor is to help you plan a personal curriculum); you do not need to request the mentors’ permission before submitting your application. At least one of the mentors must have a professor title. The mentors are covering the categories Systems Neuroscience, Neural Computation and Theoretical Neurosciences, Neurotechnologies and Neuromorphic Engineering. Please click on the links to learn more about the mentors’ research.

Additional Information

Note for applicants with a Bachelor’s degree from an University of Applied Sciences in relevant disciplines or with a Bachelor’s degree in a non-relevant discipline (i.e. as listed above):

Admission is possible, but the minimum average grade required is 5.0 (based on the Swiss Grading System). If you are a graduate of a German or Austrian Fachhochschule (University of Applied Science), you need a grade average not worse than 2.0 (based on the German/Austrian system) to be eligible for admission. Admitted students will need to complete additional coursework in the fields of neuroscience, physics, computer science, engineering, or biology. This will be decided by the admission committee on a case-by-case basis.

The Neural Systems and Computation Master's program at the University of Zurich offers a range of financing options for prospective students. Tuition fees are structured to ensure accessibility while supporting high-quality education. Domestic and international students pay an annual fee, which covers administrative costs, access to university facilities, and participation in program activities. The standard tuition fee for international students is approximately CHF 1,000 to CHF 2,000 per semester, although exact figures may vary depending on specific academic regulations and potential fee adjustments. Swiss residents benefit from lower tuition rates, often around CHF 600 to CHF 1,200 per semester.

In addition to tuition fees, students may incur costs related to living expenses, including accommodation, food, transportation, study materials, and personal expenses. The University of Zurich recommends an estimated budget of around CHF 1,500 to CHF 2,000 per month for students residing in Zurich, which includes rent, food, insurance, and leisure activities. Students are encouraged to explore various financial aid opportunities to support their studies.

The university provides several scholarships and funding programs for both domestic and international students. These include merit-based scholarships awarded on academic achievement, as well as need-based grants for students demonstrating financial hardship. Specific scholarships aimed at students enrolled in Neural Systems and Computation or related fields may also be available through national or private foundations. Students can apply for these scholarships through the university's dedicated application portal, often requiring submission of academic transcripts, motivation letters, and proof of financial need.

In addition to university-based funding, students are encouraged to seek external sources of financing, such as governmental awards, private scholarships, or student loans offered by banks and financial institutions. Swiss students may benefit from government support programs, including student loans and grants provided by the Swiss government or cantonal authorities. International students should explore scholarship opportunities in their home countries or international organizations that support students studying in Switzerland.

Part-time employment is another viable option for students to finance their studies. The University of Zurich allows international students to work part-time during their studies, often up to 15 hours per week on campus or within Zurich. This not only provides additional income but also valuable work experience within the academic environment. Students are advised to balance employment with their academic responsibilities to maintain satisfactory progress in the program.

In summary, financing a Neural Systems and Computation Master's program at the University of Zurich involves managing tuition fees, personal expenses, and exploring various financial aid options. Scholarships, external funding, part-time work, and government support play important roles in enabling students to pursue their education without undue financial burden. Prospective students should consult the university’s official financial aid office for the most current and personalized information regarding available funding opportunities and application procedures.

Expenses

Living expenses depend very much on the individual student. These figures should therefore be regarded as a guideline only (in CHF): 

The expected minimum cost of living for students therefore comes to a total of CHF 1,750 per month. Course fees come to around CHF 770 per semester.