Student assistant - general Computational Neuroscience

Job Description

Are you interested in computational neuroscience? Can you program in Python? 

Our research group studies spatial naviagation and learning and memory using computational models. We are continually looking for students to help with our research projects. Tasks may include writing Python scripts, creating unit tests, documenting existing scripts, analysing neural and behavioural data. We use techniques from deep reinforcement learning, spiking neural networks, etc.


How to Apply

Send your CV together with your most recent transcripts as a single PDF by email to Vinita Samarasinghe at samarasinghe@ini.rub.de . 

Please note that it takes a few weeks to evaluate your application and then approximately 6 weeks to process the paperwork. Hence you should apply at least 8 weeks before the beginning of the semester.


Requirements

  • You must be currently enrolled at a German university and maintain this status for at least one year from the start of your contract,
  • be able to program in Python,
  • communicate in English fluently,
  • work well in a group. 

 


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