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the fellow Prof J. L. Bamber, University of Bristol (https://research-information.bris.ac.uk/en/persons/jonathan-l-bamber), Prof X. Zhu (https://www.asg.ed.tum.de/en/sipeo/home/) and Dr M. Passaro in
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for constraining the spin of the compact object being lensed which will involve both theoretical and computational modelling. If you wish to discuss any details of the project informally, please contact: Prof
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Theoretical High Energy Physics/Mathematical Physics. The position is associated with a research program “Quantum Quenches from Quantum Fields”, which is financed by The Villum Foundation and directed by Prof
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. He/she/they will learn and apply state-of-the-art molecular and cell biology technologies established in our team, ranging from in vivo disease models to multi-omics and single cell analysis
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colleagues: This PhD position is part of a larger project, funded by the US Army Research Institute for fundamental research. The research team consists of dr. Sjir Uitdewilligen (Maastricht University), prof
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interdisciplinary research team. We study tumor evolution and immune microenvironment adaptation by combining functional genomics, experimental model systems, patient samples, and computational biology (Brägelmann et
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, funded by the US Army Research Institute for fundamental research. The research team consists of dr. Sjir Uitdewilligen (Maastricht University), prof. dr. Ramón Rico (Universidad Carlos III, Madrid), and
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applications towards materials science. Generative machine learning models have emerged as a prominent approach to AI, with impressive performance in many application domains, including materials discovery
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skills Interest in PhD Thesis Knowledge in inverse problems and forward models Willingness to be mobile (work in international projects, conferences, etc.) Admission Requirements Completed master's
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application! Your work assignments We are looking for one PhD student working on generative AI/machine learning, with applications towards materials science. Generative machine learning models have emerged as a