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. The position is part of the project “Understanding of, and Explanations with, Large Language Models”, which is funded by the Volkswagen Stiftung and associated with the Cluster of Excellence “Machine Learning
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., in the field of modeling of sector-coupled energy systems (electricity, gas, district heating), scalable control and stability analysis of energy systems using dissipativity theory, merging market
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Bioinformatics (full or part time) The Computational Life Sciences group develops and applies novel mathematical and computational approaches as well as software tools for data analysis and modeling. The spectrum
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' prognosis or treatment decisions. For modeling, we use both public and proprietary clinical and research data greatly enriched by our own repository of digital pathology images. A further focus lies on
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molecular data Your profile PhD in computer science, mathematics, physics or related fields Experience in machine learning and AI, with proven codebase in public repositories Experience or strong willingness
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Requirements: We require a PhD in a relevant subject area such as climate physics, paleoclimate, oceanography, mathematics, or related field and experience working with climate models and their
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key periods for simulations with the higher resolution EC-Earth model Requirements: We require a PhD in a relevant subject area such as climate physics, paleoclimate, oceanography, mathematics
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 2 months ago
of novel AI methods Work on generative AI or probabilistic models Analysis of medical and/or molecular data Your profile PhD in computer science, mathematics, physics or related fields Experience in machine
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signalling cues that are influenced by YAP/TAZ in a new mouse model Characterisation of the mechanisms by which YAP/TAZ are regulated in cytoplasmic signalling pathways Your qualifications: PhD in Biology
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is to understand the evolutionary driven force by which plants adapt to varying (extreme) environments on their metabol(om)ic landscape. Studies in this direction will be carried out in model organisms