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-chemical-physics/ ) led by Prof. Alexandre Tkachenko at the Department of Physics and Material Science, we are looking for a PhD candidate to perform molecular dynamics simulations of different genetic
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materialists, electrical engineers, and computer scientists of TUD, RWTH Aachen and Gesellschaft für Angewandte Mikro- und Optoelektronik mbH (AMO ) in Aachen, Forschungszentrum Jülich (FZJ ), Max Planck
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(Health and Society Group) and Prof. Arjan Stegeman (Faculty of Veterinary Medicine, Utrecht University). Your qualities A completed (or about to be completed) MSc degree in data science, computer
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this initiative, 15 early-stage doctoral candidates (DCs) will be trained through a comprehensive, interdisciplinary program spanning material science, device physics, computer architecture, hardware prototyping
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this initiative, 15 early-stage doctoral candidates (DCs) will be trained through a comprehensive, interdisciplinary program spanning material science, device physics, computer architecture, hardware prototyping
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this initiative, 15 early-stage doctoral candidates (DCs) will be trained through a comprehensive, interdisciplinary program spanning material science, device physics, computer architecture, hardware prototyping
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that are technically well-grounded and at the same time represent stakeholder preferences. The integrated Research Training Group (RTG) will provide doctoral researchers with an attractive qualification program, foster
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therefore teams up materialists, electrical engineers, and computer scientists of TUD, RWTH Aachen and Gesellschaft für Angewandte Mikro- und Optoelektronik mbH ( AMO ) in Aachen, Forschungszentrum Jülich
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methodology to better understand the safety and performance risks. Finally, multiscale simulations will be used to map learnings from laboratory-based systems (up to10 kW) to predict the behaviour and
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PhD Studentship: Optimisation of Liquid Metal Filtration and Cleanliness in Nickel Based Superalloys
-supervision by Dr Mark Hardy. The industry aligned EPSRC DigitalMetal CDT offers a four year training programme on integrating data driven with physics-based models of products equipping students with