Enrolment options

Praktikum Computational and Systems Neuroscience (WiSe25/26—Gao)

Simulations, Analyses, and Machine Learning Methods in Computational Neuroscience (TN-MPR)

This block seminar is a 2-week project-based course where we will discuss the mathematical foundations of common methods in computational neuroscience, and implement them in python.

You will work in groups to identify relevant scientific papers, come up with a modeling, analysis, and/or machine learning project based on methods in an existing paper(s), formulate a tractable question, implement models and analyses, apply them on openly available neural datasets, and communicate your findings. See Neuromatch Academy's Computational Neuroscience Course Project page as an example of the scope: https://compneuro.neuromatch.io/projects/neurons/README.html

The seminar will have a coordination meeting in January for group formation and topic choice. Then it runs for 2 weeks in February or March (TBD), where we will meet daily in a hackathon fashion to execute the project.

Dates:
- Initial meeting: Wednesday, January 21, 2026, 10am-12pm;
- Hackathon period: two weeks between February 2-March 6, 2026 (decided based on group availability)."
 
Prerequisites: familiarity with the scientific python ecosystem (numpy, scipy, matplotlib, etc.) and introductory systems or cognitive neuroscience is required, and experience with deep learning (e.g., pytorch) is not necessary, but helpful.
 

This course is offered in English, and is a part of the Data Science Praktikum module.

Guests cannot access this course. Please log in.