16 assistant-professor-computer Postdoctoral research jobs at Aarhus University in Denmark
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international quality. In your daily work, you will work closely with an interdisciplinary team of scientists and clinicians, combining cutting-edge computational approaches with experimental validation. Your
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information can be obtained from Professor Mogens Nicolaisen (mn@agro.au.dk ), Tenure Track Assistant Professor Enoch Narh Kudjordjie (enochnarh@agro.au.dk), or Professor Mette Vestergård (mvestergard
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degree programme. Approximately 500 employees from around the world are employed at the department, which houses modern laboratory, core, and animal facility infrastructures. English is the preferred
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degree programme. Approximately 500 employees from around the world are employed at the department, which houses modern laboratory, core, and animal facility infrastructures. English is the preferred
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with Professor Baudoin and other members of the probability and analysis groups. Projects may include, but are not limited to: Analysis on metric spaces including fractals Heat kernel estimates and
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consist of: Independent research of high international quality. Scientific publication of results as well as popular communication. You will report to Assistant Professor Line Staun Larsen. Your competences
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-field, and field-scale research facilities, advanced computing capacities as well as an extensive national and international researcher network. The department consists of nine research sections with
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Are you interested in X-ray imaging and biomineralization and in contributing to an international interdisciplinary Human Frontier Science Program funded project on skeletal adaptations in
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Aarhus University with related departments. Contact information Before applying or for further information, please contact: Associate Professor Aurelien Dantan, +4523987386, dantan@phys.au.dk . Deadline
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computational models to map co-expression networks and predict systemic disease transitions. Characterise intestinal microbiome changes and their correlation with inflammatory diseases. Computational modelling