159 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" positions at Nature Careers in Germany
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The Faculty of Engineering at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) invites applications for an Assistant Professor of Machine Learning in Digital Health (salary group W1
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the reference number 27697, via our online portal: Apply now via https://jobs.uksh.de/job/Kiel-PhD-%28mfd%29-Statistical-Genetics-Machine-Learning-Schl-24105/1279933701/ For more information visit: www.uksh.de
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well as basic research with the combined tools of immunology, microbiology, virology, cell biology and molecular biology. For more information, please see https://www.mhh.de/hbrs/zib MD/PhD Molecular Medicine:The
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will also profit from the vibrant research community around machine learning of the SCADS.AI center (https://scads.ai ) and the recently granted Excellence Cluster REC² – Responsible Electronics in
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plate array microscope for simultaneous time-lapse video microscopy, enabling high-throughput single-cell analyses of rapidly migrating cells. You will be responsible for Developing new machine learning
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The Center for Molecular Bioengineering ( B CUBE) ( https://tu-dresden.de/cmcb/bcube ) and its partner institutions, the Biotechnology Center (BIOTEC) and the Center for Regenerative Therapies
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programme Biochemistry & Molecular Biology, and other relevant programmes at the University of Bayreuth. The ability to teach in English and German is expected. The general administrative requirements
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theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers the opportunity to work with
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regulations. Further information on data protection and the processing of personal data can be found at: https://www.isas.de/en/datenschutz . The closing date for applications is March 25, 2026. Please apply
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investigations as well as analyzing and interpreting the results of these investigations developing and testing innovative spinning technologies and modifying existing machine technology preparation of scientific