Job Description
The successful applicant will work on a collaborative project (within the Collaborative Research Center “Extinction Learning” (SFB 1280)), together with experimentalists, to:
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Analyze learning dynamics in behavioral, neural, and psychophysiological data, which will be collected by other projects within the SFB 1280.
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Compare the learning dynamics between individuals, species, learning phases and learning paradigms.
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Develop analytical methods and algorithms for studying learning dynamics in behavioral, neural, and psychophysiological data.
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Develop and investigate computational models of biological learning processes and their dynamics.
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Coordinate research with other participating projects.
The Cheng Lab 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.
We are committed to providing a supportive work environment for female researchers, in particular those with young children. Our university provides individual 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 lisa.grunau@rub.de In addition, at least two academic references must be sent independently to the above email address. Travel costs for interviews will not be reimbursed.
Requirements
Candidates must have:
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a doctorate degree in neuroscience, physics, mathematics, electrical/biomedical engineering or a closely related field,
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relevant experience in mathematical modeling,
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excellent programming skills (e.g., Python, C/C++, Matlab),
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excellent communication skills in English
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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.