502 machine-learning "https:" "https:" "https:" "https:" "https:" "Dana Farber Cancer Institute" PhD positions in Germany
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Schenefeld, Germany www.xfel.eu Where to apply Website https://cockpit.as-mediendesign.de/jump1/121381 Requirements Research FieldPhysicsEducation LevelMaster Degree or equivalent LanguagesENGLISHLevelGood
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embedded in the Bremen Research Cluster for Dynamics in Logistics (LogDynamics) (http://www.logdynamics.de ). LogDynamics is a cooperative network of research groups from five different departments
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the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data
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or TOEFL Submit application to https://www.grk2338.med.uni-muenchen.de Accommodation The International Office helps visiting academics, PhD students, and postdocs who are travelling to Munich for a set
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development is important to us – we support you specifically and individually e.g., through training and networking opportunities specifically for doctoral candidates (JuDocS): https://go.fzj.de/JuDocs FAIR
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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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on average expenditure: Rent, including ancillary costs (in Erlangen, Nuremberg and surrounding areas): 410 EUR Food: 198 EUR Clothing: 46 EUR Travel costs (public transport and/or car): 89 EUR Study materials
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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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Additional information on beginning, duration and mode of study The starting date of the PhD project is flexible. The initial funding period is usually three years. Find out more at https://www.bgc-jena.mpg.de
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tailored computational methods are needed. This project aims at combining probabilistic machine learning methods with prior knowledge in the form of graphs to analyze and predict food-effector systems. Key