87 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UNIV" "UNIV" "Univ" scholarships at Nature Careers
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of novel probabilistic deep-learning models that automatically extract mechanistic and statistical knowledge from your in vivo perturbational omics data. This interdisciplinary atmosphere has been a main
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breast cancer patients, explore the activation mechanism of antiviral defense pathways in cell cultures and perform bioinformatics analysis of data. The work will be performed in a modern molecular biology
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. Research at the DKFZ is organized into the following programs with a lot of interaction and interdisciplinary PhD projects available across different topics: For more information about the groups and their
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position in the area of machine learning and computer simulations. The focus of the PhD project will lie on developing machine learning models for clustering, classification, regression and reinforcement
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, (bio)informatics, and multimodal data analysis. The research group focusses on the mechanisms of Hypothalamic-Pituitary-Gonadal (HGP) axis regulation that governs human reproduction. The group
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. The research group at GEOMAR complements these data and researches the role of fine-scale eddies by using high-resolution models of the ocean and the atmosphere. WHIRLS consists of 4 partners in France, Sweden
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collect and analyse health data, identify risks, advise government and experts, and develop new scientific methods. We are based in Berlin, Wildau and Wernigerode. Get started now Apply directly through the
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at the Institute of Medical Informatics within the research group “Medical Data Integration Center (MeDIC)” led by Dr. Michael Storck and is embedded in the DFG-funded Collaborative Research Centre 1748, Principles
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learning Distributed and federated training The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another
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Learning with Graphs led by Prof. Nils M. Kriege. Our research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains