151 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Ulster University" 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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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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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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the Interreg project webpage ( https://www.sn-cz2027.eu/de/projekte/prioritat-2-klimawandel-und-nachhaltigkeit/100781629_beech ). For TUD diversity is an essential feature and a quality criterion of an excellent
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tools like ViennaRNA and NUPACK) and MD simulations (e.g., with GROMACS). Strong skills in statistical data analysis and machine learning in Python and R are expected, along with experience working in
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W3 Endowed Professorship for “Hemodynamic Modeling in Atherosclerosis- (f/m/d) KSB Foundation W3 end
exclusively in electronic form and in accordance with the “Applicant Guideline Format Template” and the “Applicant Form” of the Medical Faculty Mannheim for W3 professorships (see https://www.umm.uni
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printing) and computer-assisted load analysis Expertise in the numerical simulation of realistic loading scenarios of the musculoskeletal system Your Profile: The future position holder has an academic
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postdoctoral research track record and are expected to build and lead a group to pursue a high-quality research programme. Current research interests within the Division of Condensed Matter Theory (https