1,551 machine-learning "https:" "https:" "https:" "https:" "https:" "The University of Edinburgh" positions in Germany
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funding via an employment contract with the Max Planck Institute for the History of Science (MPIWG) or with Technische Universität Berlin and will have the possibility to teach. Two employment contracts
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part of the Forschungsverbund Berlin (https://www.fv-berlin.de/ ) and the Leibniz Association (https://www.leibniz-gemeinschaft.de ). You can find more details on the institute webpage: https://www.ikz
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metamaterials. The successful candidate participates actively in the qualification program and general scientific activities of D³. More information can be found at https://tu-dresden.de/ing/forschung
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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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outstanding infrastructure ENVIRONMENT: A creative work environment at a leading research facility, located on an attractive research campus at the TZA Aachen https://tza-aachen.de and the Forschungszentrum
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PostDoc/Senior Scientist - Process and Plant Design in the Field of Liquid Organic Hydrogen Carriers
) appointments FLEXIBILITY: Flexible working time models, including options close to full-time ( https://go.fzj.de/near-full-time ), allow you to tailor your working hours to suit your individual needs HEALTH
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for doctoral students (HITEC): https://www.hitec-graduate-school.de/home FAIR REMUNERATION: Depending on your qualifications and assigned responsibilities, you will be classified according to pay group 13 (75
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specifically and individually e.g., through training and networking opportunities specifically for doctoral candidates (JuDocS): https://go.fzj.de/JuDocs VACATION: You will receive 30 days of vacation SUCCESSFUL
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proof of immunity against measles. Do not overlook the inclusion of Academic Europe in your application. Where to apply Website https://www.academiceurope.com/ads/research-data-scientist-in
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data handling Strong self-initiative and willingness to learn and to quickly gain an understanding of new subject areas Joy in working independently, as well as within a team Strong problem-solving