Student assistant for a helping in a project on computational neuroscience Theory of Neural Systems

Job Description

We are looking for a motivated student assistant for the Theory of Neural Systems Group of Prof. Dr. Laurenz Wiskott at the Institut für Neuroinformatik at Ruhr-Universität Bochum. The work will be focused on computational neuroscience. The student will assist a Ph.D. researcher in developing a computational model of memory. The tasks would be helping with programming and also preparing some graphs. If you are interested in the field of machine learning there are a lot of opportunities to learn and enhance your skills in this project. You can also learn how research is conducted in academia if you are considering a Ph.D.

- Enrolled at a German university as a master student
- Programming experience in Python
- Good Knowledge of English
- Basic Knowledge of machine learning methods

- Programming experience in Tensorflow/Keras
- Knowledge of Latex

How to Apply:
A short statement of your motivation and a single PDF file including your CV as well as your transcript of records to with CC to

Contract Conditions:
A part-time position (8-12 hours per week) starting immediately and initially limited for 6 months with the possibility of extension.

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