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using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts generated in the scattering
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, the details of the process are not yet fully understood. Mechanistic learning, the combination of mathematical mechanistic modelling and machine learning, enables a data-driven investigation of the processes
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demands. To break this bottleneck and cut simulation time by orders of magnitude, you will design and implement surrogate models that learn the behavior of full‑physics codes using modern machine‑learning
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). Tasks The successful candidate will conduct cutting-edge empirical research in at least one of the following areas natural resources and environment, digitalisation, AI and smart technologies in
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(starting at TV-L E13 2/3). Tasks The successful candidate will conduct cutting-edge empirical research in at least one of the following areas productivity and efficiency measurement at various levels, policy
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organisms age or how our DNA is repaired, to how epigenetics regulates cellular identity or neural memory. Activities and responsibilities The research group of Katja Luck offers the following PhD project
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for Offspring Health (Diefenbach lab) Variant Surface Antigen Expression in chronic Plasmodium falciparum carriage (Portugal lab) Dissecting the Molecular Pathways of NK Cell Memory (Romagnani lab) Dissecting
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on retention processes are still poorly understood. The PhD thesis is part of the joint project TRANSFER, which is jointly funded by the Federal Ministry for Research, Technology and Space (BMFTR) and the
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organisms age or how our DNA is repaired, to how epigenetics regulates cellular identity or neural memory. Activities and responsibilities The research group of Siyao Wang offers the following PhD project
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Description The International Max Planck Research School for Quantitative Behavior, Ecology and Evolution from lab to field (IMPRS-QBEE) is looking for two motiviated PhD students to start latest in