Wednesday, January 8, 2014

[Comp-neuro] PhD position - computational modelling



Dear colleagues,

The Collaborative Research Center (CRC) 1052 "Obesity mechanisms" at the Leipzig University Hospital is offering a PhD studentship in computational modelling under the supervision of Dr Jane Neumann and Dr Annette Horstmann. Within the project, computational modelling will be used to investigate decision-making and learning in humans by combining genetic, behavioural and magnetic resonance imaging (MRI) data from different modalities.
 
The PhD position will be based at the Max Planck Institute for Human Cognitive and Brain Sciences in the beautiful city of Leipzig. Both Leipzig‘s long tradition in conducting neuroscientific research and the ultra-modern equipment at the Institute provide an environment that offers new perspectives in neuroimaging research. Further, the position will be part of the CRCs Integrated Research Training Group. This graduate program offers interdisciplinary qualification in various research methods and transferable skills, and provides support in career planning and in establishing an own scientific network.
 
Applicants should hold a Master's degree (or equivalent) in one of the following disciplines: computational or cognitive neuroscience, computer science, mathematics, physics, cognitive science or related. Prior experience in the field of computational neuroscience and/or neuroimaging are of advantage. Sound knowledge of statistics and excellent programming skills are essential. A good command of written and spoken English is requested of all applicants.
 
Please send your application as a single pdf-file to neumann@cbs.mpg.de referring to 'Modelling SFB 1052'. Complete applications include cover letter, CV, letter(s) of recommendation, and copies of university degrees and additional certificates.
 
Informal enquiries should be made to Dr Jane Neumann (neumann@cbs.mpg.de, +49 (0) 341 99 40 26 21).
 
The salary is based on the German E 13 TV-L salary scale. In order to increase the proportion of female staff members, applications from female scientists are particularly encouraged. Disabled applicants are preferred if qualification is equal.
 
Deadline for application: until position is filled



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