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for candidates with strong backgrounds (preferably PhDs) within mechanical engineering, manufacturing engineering, materials science, applied mathematics or physics. Specific disciplines will involve heat transfer
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mathematical and analytical models to predict coil loss, facilitating the optimal design of HPMCs Constructing a large-signal platform to measure coil loss of HPMCs Exploring innovative solutions, such as new
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Systems Transformation with Novel Foods based on alternative proteins (EPIC-SHIFT), we seek a proactive candidate with a strong background in generating experimental data and integrating with mathematical
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magnetism. Qualified applicants must have PhD degree in physics, astronomy, mathematics, engineering, computer science or similar. Experience with numerical methods, preferably within open-source software
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Thermodynamics, Transport Processes and Mathematical Modelling. AT CERE has a total staff of approx. 50, of which 6 is faculty. Technology for people DTU develops technology for people. With our international
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develop mathematically-founded machine learning algorithms for video analyses. Demonstrated experience in developing and evaluating machine learning models. A history of publishing in peer reviewed journals