Fachbereich 7

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Projects at the intersection of neuroscience and machine learning
DozentIn:Prof. Dr. rer. nat. Tim Christian Kietzmann, M. Sc. Philip Sulewski
Veranstaltungstyp:Seminar (Offizielle Lehrveranstaltungen)
Ort:50/E07: Mi. 10:00 - 12:00 (12x), 50/E04: Mi. 14:00 - 16:00 (13x)
Semester:SoSe 2024
Zeiten:Mi. 10:00 - 12:00 (wöchentlich), Ort: 50/E07, Mi. 14:00 - 16:00 (wöchentlich), Ort: 50/E04
Erster Termin:Mittwoch, 03.04.2024 14:00 - 16:00, Ort: 50/E04
Beschreibung:Content and goal:
In this course, you will work on your own in-depth project, either alone or (preferably) with at least one other student. The projects can be chosen from a list provided by the instructors or decided jointly with students and instructors. The course will begin with in-depth discussions to help you decide the details of the projects. In the subsequent weekly meetings, you will provide brief summaries of your progress - what is done, what are the roadblocks, and what are the next steps, and the group and instructors will provide guidance on how to proceed further. Students will be required to review each-other’s code to learn to write clearly/accessibly, and to take the perspective of an external code-reviewer. By the end you will have completed a project at the intersection of neuroscience and machine learning, you will have learned to review code, to communicate problems, and you will have gotten an in-depth insight into the research field as such. You will be required to document your project in the form of a research paper or a thesis.

This is a work intensive course with two meetings each week. One meeting is to be an active part of the lab colloquium: to inform yourselves about other work in the area, to contextualise your work, and to present your plans and work. Another weekly meeting is for course-members only and will be used to discuss the project, code, progress, roadblocks, etc.

Course requirements:
Master students or advanced bachelor students with the following experiences/coursework completed:
- Proficiency in programming with python
- Introduction to Linear Algebra
- Neuroscience basics (e.g. Action and Cognition (Vision))
- Implementing ANNs in Tensorflow or Machine Learning for Cognitive Computational Neuroscience

Number of participants:
The number of participants of this course is limited to ensure that we can offer the best in-depth project guidance and support. If more students than the maximum number apply, we will choose a subgroup based on fulfilment of course criteria/past experience and motivation letters. The exact procedure will be communicated in the first session once we can tell how many students exactly are actively parttaking.

Course application:
If you are interested in taking part in the course, please provide proof that you fulfil the course criteria (see above) as well as a short motivation letter (250 words max).

If you participate with a *standalone* project your grade will be based on your project, documentation and your active participation in the weekly meetings. If you take this seminar alongside your thesis work, no credit/grade can be given.
zur Veranstaltung in Stud.IP