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Field
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and skills: You hold a PhD in Bioinformatics, Computational Biology, Genomics or a related field. You bring proven expertise in deep learning and statistical modelling of biological data. You have
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genomic approaches Application of the modeling approaches in relevant downstream tasks Co-development of high-performance computing AI training codes for the first European Exascale Supercomputer JUPITER
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exchange and interaction state of the art computing infrastructure (HPC) salary assigned according to the pay scale UKF standard social benefits, e.g. UKF job ticket UKF Your tasks: develop and optimize
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to supervise PhD, Master and Dr. med (thesis as part of medical studies in Germany) students. The fellow will also have the opportunity to teach as part of the institute’s Masters and doctoral program but will
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to teach as part of the institute’s Masters and doctoral program but will not be required or expected to do so. The salary is paid according to the German TV-L system (the salary agreement for public service
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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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scaling and generalization behavior Roll out the model to the global user community Requirements PhD or MSc in computer science, physics, mathematics or a related discipline Experience with large-scale HPC
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available in the further tabs (e.g. “Application requirements”). Programme Description The programme is intended for outstanding junior post-doctoral scientists from Germany, Austria and Switzerland from all
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, cutting edge research towards scalable quantum computing A research track record commensurate with our ambition Our Offer: We work on the very latest issues that impact our society and are offering you the
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the faculties of medicine and computer science at TUM, as well as the Munich Center for Machine Learning (MCML). It is a great place for interdisciplinary research between medicine and data science. We