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combining state-of-the-art machine learning with physicochemical knowledge and molecular modeling. Representative publications from our group include: https://doi.org/10.1038/s41467-025-63947-5 https
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combining state-of-the-art machine learning with physicochemical knowledge and molecular modeling. Representative publications from our group include: https://doi.org/10.1038/s41467-025-63947-5 https
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approaches for drug design by combining state-of-the-art machine learning with physicochemical knowledge and molecular modeling. Representative publications from our group include: https://doi.org/10.1038
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, and coordinate actions while remaining autonomous and specialized. The research combines generative video modeling, self-supervised learning, memory, test-time adaptation, and decisionmaking, with
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advanced machine-learning and AI methods for complex engineering and industrial systems, with a particular focus on improving their reliability, availability, and operational performance while
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collaboration with the Intelligent Maintenance and Operations Systems (IMOS) Laboratory at EPFL ( Prof. Olga Fink ). IMOS develops advanced machine-learning and AI methods for complex engineering and
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basic science into medical knowledge and healthcare innovations. The Pediatric Disease Modeling Lab (https://dbe.unibas.ch/en/research/data-driven-modelling-analysis/pediatric-disease-modeling-lab
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Swiss Federal Institute of Technology Lausanne, EPFL | Lausanne, Canton de Vaud | Switzerland | about 2 months ago
-learning approaches for materials discovery and modeling. A doctorate is required at the starting date. A successful candidate is expected to develop an independent and competitive research program in
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care. Our work combines statistical and mechanistic mathematical modeling, causal inference, and machine learning, applied to longitudinal multi-omics data from pediatric cohorts spanning diverse socio
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and mechanistic mathematical modeling, causal inference, and machine learning, applied to longitudinal multi-omics data from pediatric cohorts spanning diverse socio-economic and geographical contexts