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Job Id: 10797 Limited to 2 Years | Full-time with 38.5 hours/week | German salary grade E 13 TV-L | The medical faculty in collaboration with the mathematics department of the University of Münster
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. Qualifications: PhD in machine learning, with experience in applications in computer vision or medical image analysis. Strong publication record in top venues (e.g., CVPR, MIDL, MICCAI, IPMI, PAMI, TMI, MIA
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collaboration partners. The Center possesses the unique possibility to investigate cutting-edge interdisciplinary questions within the theoretical and fundamental aspects of Mathematics, Physics, and Computer
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research on theoretical and experimental subatomic physics, mathematical and high-energy physics, plasma and fusion physics, as well as nuclear physics. This diversity of research topics allows us to connect
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mathematical and computational techniques, it is essential to have experience in mathematical modelling / dynamical systems theory / numerical methods / coding. An ideal candidate would have a PhD, or
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. Currently, a number of mathematical models exist to describe the onset and progression of Alzheimer’s Disease and the effects of anti-amyloid therapies on disease progression. The models are informed by a
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. The Department of Mathematics and Computer Science, Hessain.AI research group “Artificial Intelligence – Deep Decision Support Systems”, led by Prof. Dr. Martin Becker, is currently accepting applications for a
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are looking for: a highly motivated researcher with at least 3 years of research experience (possibly as part of the PhD) in a field related to mathematical analysis of partial differential equations (PDEs
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closely with the Department of Mathematics at Aarhus University. In addition, your organic chemistry skills will be instrumental in developing antioxidant artificial cells. These interdisciplinary projects
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of the near critical Ising model, or the massive Thirring model. Qualifications We are looking for applicants with a PhD in mathematics or theoretical physics, with experience in mathematically rigorous