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Methodological competence: Strong programming skills, ideally including experience in deep learning and/or high-performance computing Passion for method development Very good English communication skills – both
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communication skills in English Beneficial A background in the ocean uptake of carbon and heat or mesoscale eddy parameterizations Experience with high-performance computing facilities and knowledge of Fortran
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in Applied Mathematics, Computational Science and Engineering (CSE), or related fields with outstanding academic performance Strong programming skills and experience in languages such as C/C++, FORTRAN
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economics community in Fuerth, Nuremberg and Munich are connected to the Department of Economics at FAU Nuremberg can participate in the structured Junior Faculty Development Program and have the opportunity
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, currently listed as the strongest German business school for research, and #9 in Europe for M.Sc. programs on entrepreneurship. The TUM Campus Heilbronn is a dynamic organization whose goal is to achieve
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% international students in the MA program. The visual computing lab embraces its diverse culture, and is proud to host PhD students from over 10 different countries. Our lab language is English. The position is
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performance and degradation of electrolysis in dependence on different operating modes Your Profile: Completed Master’s degree in chemical engineering, computational engineering, computational mathematics, data
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, Statistical Physics, Genome Annotation, and/or related fields Practical experience with High Performance Computing Systems as well as parallel/distributed programming Very good command of written and spoken
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doctoral degree in psychology, cognitive science, biology, computer science, medicine or an equivalent discipline Relevant research experience or interest in the field of “Decision Neuroscience
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good publication track record Above-average master’s degree in computer science, electrical/ mechanical engineering, applied mathematics, or a similar engineering-oriented quantitative discipline