61 parallel-computing-numerical-methods uni jobs at Technical University of Munich in Germany
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, or learning sciences. You are interested in interdisciplinary collaboration and working in research teams. You have very good knowledge of social science research methods and statistics. You have
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research methods and statistics. - Experiences with research syntheses (e.g., meta-analyses) and video data analyses would be an advantage. - You have very good written and spoken Eng-lish skills and good
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PostDoc (m/w/d) position on “Biological engineering of novel gene reporters for Electron Microscopy”
the systematic analysis of function-ultrastructure relationships in brains with implications for our understanding of neuropsychiatric diseases and inspiration for neuromorphic computing. Your Ideal Qualifications
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empirical research with design practices from a comparative perspective. CUSP aims to approach urban and peripheral spatial research through ethnographic and qualitative methods. We focus on the critical
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• Conduct statistical consultation for Helmholtz scientists and industry partners • Evaluate and apply novel statistical methods in the context of applied research • Write statistical reports on experimental
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methods (such as Machine Learning, Metric Learning, Reinforcement Learning, Graph Representation Learning, Generative Models, Domain Adaptation, etc.) for Design Automation applications. To this end, we
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parameters to understand hydraulic thermal processes, develop innovative monitoring systems, evalua-tion and implementation methods like geothermal potential assessment as well as numerical reservoir modelling
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knowledge and practical experience in the field of radiation detectors. Experience in the design and performance optimization of neutron detectors is highly advantageous. You work methodically and demonstrate
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from the perspective of flight mechanics and fluid mechanics. A sound experience in programming in C/C++ and Cuda is very desirable, the motivation to independently develop, implement and test numerical
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very good Master’s degree in Computer Science, Medical Informatics, Business Informatics or a related field. Practical experience as a full-stack developer for cloud-native and/or on-premise applications