Postdoctoral Position in Computational Neuroscience Computational Neuroscience

Job Description

The position is part of the Collaborative Research Center “Extinction Learning” (SFB 1280) and entails the following duties:

  • Analyze learning dynamics in behavioral, neural, and psychophysiological data, which will be collected by other projects within the SFB 1280.

  • Compare the learning dynamics between individuals, species, learning phases and learning paradigms.

  • Develop algorithms to analyze the learning dynamics.

  • Develop and study computational models of learning dynamics.

  • Coordinate research with other participating projects.

The research group is highly dynamic and uses diverse computational modeling approaches including biological neural networks, cognitive modeling, and machine learning to investigate learning and memory in humans and animals. For further information see www.rub.de/cns.

The Ruhr University Bochum is home to a vibrant research community in neuroscience and cognitive science. The Institute for Neural Computation combines different areas of expertise ranging from experimental and theoretical neuroscience to machine learning and robotics.

We are committed to providing a supportive work environment for female researchers, in particular those with young children. Our university provides mentoring and coaching opportunities specifically aimed at women in research. We have a strong research network with female role models and will provide opportunities to network with them. Wherever possible, events will be scheduled during regular childcare hours. Special childcare will be arranged if events have to be scheduled outside of regular hours, in case of sickness and during school or daycare closures. Where childcare is not an option parents will be offered a home office solution.


How to Apply

Please send your application, including CV, transcripts and research statement electronically, as a single PDF file, to samarasinghe@ini.rub.de. In addition, at least two academic references must be sent independently to the above email address. The deadline for applications is January 3rd, 2022. Travel costs for interviews will not be reimbursed.


Requirements

Candidates must have:

  • a doctorate degree in neuroscience, physics, mathematics, electrical/biomedical engineering or a closely related field,

  • relevant experience in mathematical modeling,

  • excellent programming skills (e.g., Python, C/C++, Matlab),

  • excellent communication skills in English

  • the ability to work well in a team.

Research experience in neuroscience would be a further asset.


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