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documentation. - Supporting the team in preparing and implementing various informed machine learning models for benchmarking and analysis. Desirable: - Currently enrolled in a Bachelor's or Master's program in
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, computer science, medicine, pharmacology, and physics. ISAS is a member of the Leibniz Association and is publicly funded by the Federal Republic of Germany and its federal states. At our location in
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the third year. The position is subject to the approval of project funding, which is still pending. Your tasks The advertised radioecology-oriented doctoral program is being carried out in a joint project
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supervision collaboration in national or international research projects (optional) Requirements: university degree in Computer Science, Computational Linguistics, Mathematics or a related field solid knowledge
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interdisciplinary and transdisciplinary research at the interface between data science, life sciences, and bioeconomics. The professor will closely cooperate with the TUM School of Computation, Information and
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Interactions in a Changing World” is an interdisciplinary research initiative of geoscientists, biologists, and computer scientists at the Universities of Tübingen and Hohenheim and the Senckenberg Institution
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. Applicants should have experience with tissue culture and standard molecular biology methods. Basic knowledge of computer programming (using the R software environment) and hands-on experience working with
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outstanding students from all over the world to apply for PhD positions in our renowned PhD program. Based in Hamburg, our program offers excellent training and top-level structured supervision in climate
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to scientists and investigate possible applications of ML in fields like Chemistry, Numerics, Computational Biology, Astrophysics, Heliophysics etc. You will be involved in all phases of this process. You will
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degree (or equivalent) in Data Science, Computational Biology, Bioinformatics, Computer Science, Physics or a related field Solid programming skills and knowledge in deep learning, statistical modelling