PhD position in computational neuroscience Theory of Neural Systems

Job Description

We are looking for an outstanding candidate who will be working on a system-level model of spatial navigation with the hippocampus as one of its central areas. We use methods from neural networks and machine learning. It is also planned to simulate experiments done with rat and/or mice by our experimental partners.

The position is part of a joint team with Prof. Sen Cheng working on developing a system-level model of hippocampal function for memory and navigation. This is being done in close interaction with a team working on similar questions from the machine learning perspective.

There is a teaching load of 3 hours per week during the semester, in particular for a programming course in python.

How to Apply

Applications (CV, transcript of records for MSc and BSc, statement of purpose) should be sent as a single pdf file to Prof. Laurenz Wiskott.


Candidates should have an education (equivalent to a MSc) in computer science, physics, mathematics, electrical engineering or any related field. Required are strong mathematical and programming skills (ideally in python) as well as the ability to communicate and work well in a team.

Ruhr University Bochum is committed to equal opportunity in employment and gender equality in its working environment. To increase gender distribution in all job categories and at all levels, we strongly encourage applications from qualified women. Female applicants will be given preferential consideration when their level of qualification, competence and professional achievements equals that of male candidates, unless arguments based on the personal background of a male co-applicant prevail. Applications from appropriately qualified handicapped persons are also encouraged.

The Institut für Neuroinformatik (INI) is a central research unit of the Ruhr-Universität Bochum. We aim to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory systems and while acting in those environments through effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental approaches from psychology and neurophysiology as well as theoretical approaches from physics, mathematics, electrical engineering and applied computer science, in particular machine learning, artificial intelligence, and computer vision.

Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany

Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210