19 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" scholarships at Nature Careers in Germany
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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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The analysis of generated data and communication within an interdisciplinary team made up of people working in natural, life and computer sciences as well as medicine Presenting the research outcome in lab
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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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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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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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The Bernhard Nocht Institute for Tropical Medicine (http://www.bnitm.de/en ) is the largest Research Institute for Tropical Medicine in Germany and is the National Reference Centre for Tropical
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LMU Munich. The group is located within the Institute of Clinical Neuroimmunology (https://www.neuroimmunology-munich.de/ ). The professorship of Systems Neuroimmunology is part of the Cluster
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research environment for biophysics. Our group combines molecular dynamics simulations with machine learning techniques to understand how proteins, biomembranes, and small drug-like molecules interact
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for immobilizing these ions. Modern methods of theoretical chemistry (first principles, kinetic Monte Carlo, machine learning) will be applied to investigate diffusion phenomena and link speciation with