Student assistant for physical and virtual robotics simulations Computational Neuroscience

Jobs Description

The research group Computational Neuroscience at the Institute of Neural Computation (Institut für Neuroinformatik) is hiring a student assistant (7-10 h/week) to support the project “Modeling context-dependent acquisition and extinction learning”. Primarily you will be responsible for the manual creation and the procedural generation of virtual experimental environments using the “Blender” modeling system. In addition, you will be involved with the modeling and programming of mobile robots in virtual environments (using Blender), and the real world.

How to Apply

Please send your application by 31.03.2019, including CV and letter of motivation, as a single PDF file to Vinita Samarasinghe,


Excellent knowledge of:

  • Python
  • C/C++
  • English

Desired skills:

  • Experience with Blender as a modeling/simulation tool
  • Experience with MATLAB®
  • Basic understanding of git version control
  • Knowledge in the area of mobile robotics

In addition, the candidate should be able to work in a team and have good communication skills.

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.

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

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