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the lab of dr. ir. M. Peirlinck in the Department of BioMechanical Engineering at TU Delft. Our group combines nonlinear mechanics, computational modeling, experimental and clinical data, and machine
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estimation using data-driven dithering Subspace and DOA estimation under coarse quantization Preprint versions can be found on Arxiv. These works are representative for the type of mathematics involved
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topics such as Hamilton-Jacobi Bellman equations, stochastic optimisation frameworks, game-theoretical analysis of space logistics, high order automated differentiation, neural and Hamiltonian ODEs, data
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strands of data collection and analysis, including semi-structured interviews with undergraduate students and analysing coursework artefacts; analysing how students interpret, evaluate, and represent
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fabricate and characterize perovskite-silicon tandem solar cells using state-of-the-art facilities at the TU Delft PV Technology Center, including large-area cleanroom processing, advanced thin-film
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. Marieke de Goede. The project is funded by the European Research Council (ERC) through an Advanced Grant. For more information, see https://cordis.europa.eu/project/id/101199713. Join Us! We are looking
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: develop physics-informed and physics-grounded world models that remain reliable under partial observation, where pure physics engines fall short; design methods that achieve large speed-ups in complex
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to develop a new generation of traffic prediction methods, combining traffic flow theory with machine learning, and with that, the best of both worlds: theory and logic where necessary, data-driven where
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stabilizing the grid, reducing reliance on fossil fuels, and ensuring more effective use of renewable energy. TenneT expects 4.9 GW of large-scale battery storage is required in The Netherlands by 2030, while
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, plant biochemistry and big data (statistical) analyses including bioinformatics and scripting in Phyton, R studio, MaxQuant, Persues or related; hands-on experience in and affinity with molecular biology