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. This research is part of the Metapix Excellence Centre (2024-2029) aimed at realizing breakthroughs in integrated photonics. You will thus be part of a team of PhD students and postdocs in a constellation of
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Learning for Biomedical Data. The postholders will focus on developing and applying state-of-the-art generative models (such as VAEs, GANs, and transformer-based architectures) to large-scale biomedical
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successful team of PhD students and postdocs in a constellation of local theoretical and experimental groups. For this postdoc project, we seek a dynamic and motivated candidate with an interest in
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Excellence Centre (2024-2029) aimed at realizing breakthroughs in integrated photonics. You will thus be part of a team of PhD students and postdocs in a constellation of local theoretical and experimental
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and technical reports, as well as seminar and conference presentations Active participation in professional organizations Basic Qualifications: A PhD in Mathematics, Applied Mathematics, Computational
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, prediction of cell states, or patient stratification Contribute to the further development of model architectures (e.g., transformers, multimodal fusion, generative models) Present results at conferences and
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Jerzy Haber Institute of Catalysis and Surface Chemistry, Polish Academy of Sciences | Poland | 20 days ago
molecular architecture and the resulting structures - as the structural parameters and interfacial behavior of the multicharge surfactants - are essential for understanding their adsorption and aggregation
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is to perform your own research in a research group. The position may also include teaching on undergraduate and master's levels as well as supervising master's and/or PhD students to a certain extent
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networks (5G and WiFi 7 and their evolutions) in terms of architecture, protocols, and optimization. These networks benefit from new technologies and approaches, such as virtualization and AI, to make them
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program) and a symbolic solver computing the solution. Another example is the generation of surrogate model architectures for complex industrial systems: the generative component proposes models based