Two Post-doc positions in machine learning Theory of Machine Learning

Job Description

We are looking for a highly skilled and motivated candidate performing applied machine learning research. The candidate is expected to work on the design of a platform for industrial applications of machine learning, with a research focus on automated machine learning methods. He/she will have the opportunity to join the stimulating interdisciplinary research environment of the institute for neural computation, which spans a broad range of research directions from neuroscience to machine learning and robotics. The very competitive salary is based on TV-L E14.

The official job annoucement is found here:

How to Apply

Please direct applications to before November 15, 2020. Formal applications should include a cover letter, a CV, a list of publications, Masters and PhD certificates (if applicable), as well as the email address of a person willig to provide a letter of reference.


  • A PhD in machine learning or a closely related field is ideal. We also accept applications for PhD positions.
  • strong programming skills
  • good English language skills
  • industry experience is a plus

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