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%. High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process . An excellent technical
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, enabling Digital Twins and AI-based decision support for design and process choices. This full-time position offers access to advanced laboratories, simulation environments, and a multidisciplinary research
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of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after
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generation of commercial aircraft, combining excellent mechanical performance with low weight. In addition, their melt-processable matrix enables automated, high-rate manufacturing of components that can
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allowance. Extensive opportunities for personal and professional development. Selection process Interested? Does this vacancy appeal to you? If so, click on the button below and apply straightaway. Please add
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, and the use of discarding low-quality entanglement (cut-off time). We will use simulation and analytical calculation for doing so. As part of the Doctoral Network collaboration his position includes
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release and self-assembly into a sealing film. You will work closely with a second PhD candidate focused on molecular simulation, and with project partners at UvA and TNO. Your experiments will connect
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using PISCES (Planetary Ices Simulation Chamber for Enceladus and MoonS), currently the first facility in the world to simulate the plumes of Enceladus. This project will also investigate the structure
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how fluid dynamics can be simulated on quantum computers by designing novel quantum algorithms, implementing software, and evaluating their performance on quantum computer simulators and potentially
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limited, noisy, and low-resolution measurement data? In this project, you will develop a novel physics-informed machine learning approach that integrates physical simulations of the measurement process with