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are working to improve the built environment with the help of a broad set of disciplines, including architectural design, urban planning, building technology, social sciences, process management, and geo
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Postdoc: Machine learning for wind flow prediction in coastal dunes Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline: 6
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losses and environmental impact As a Postdoc within the EvalueWaste consortium at TU Delft, you will: Scale-up of a solvothermal process to recover metals and polymers from cardiac catheters for reuse
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shaving. Job description The rapid electrification of transport, buildings, and industry is creating unprecedented pressure on urban electricity networks resulting in Grid congestion. In particular
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microbiomes can strongly influence crop growth, nutrition and resilience, but their behaviour depends on the crop, soil, environment and the surrounding microbial community. NOAH aims to make these context
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design, urban planning, building technology, social sciences, process management, and geo-information science. The faculty works closely with other faculties, universities, private parties, and the public
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Science, Physics, Mathematics or Computer Science. You have a solid background in computational fluid dynamics (CFD) and be proficient in programming (e.g., Python, Fortran, or C++) and visualization tools
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: Within this international project, TU Delft will develop a machine learning-based forward operator to enable the assimilation of SAR imagery into the crop growth model. You will: Process SAR imagery over
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quantum and hybrid quantum-classical methods can make a real scientific difference, build reusable expertise and create the basis for future academic and public-private collaborations. At BDA, you will be
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strongly influence crop growth, nutrition and resilience, but their behaviour depends on the crop, soil, environment and the surrounding microbial community. NOAH aims to make these context-dependent