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strong background in CFD and/or DEM, A strong numerical background with proficient programming skills, Strong motivation, problem-solving skills, and the ability to work both independently and as part of a
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PhD student (m/f/d) in the field of chemistry, chemical engineering, materials science or comparable
command of written and spoken English Basic programming skills and basic knowledge in the fields of machine learning and material simulations (i.e., quantum chemistry, density-functional theory, machine
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funded by the Leibniz Collaborative Excellence program and conducted in cooperation with the Institute of Space Systems at the University of Stuttgart. The position includes setting up a multi-metal lidar
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qualifications include a Master's degree in computational biology or a related field. Prior experience with programming, statistics and biomedical research is essential, while experience with machine learning is
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Programme (DTP), offering one home and one overseas 3.5-year studentship covering full tuition fees and a standard UKRI stipend. For further details of how to apply, please click on the 'Apply' button above.
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-year Norwegian program, where 120 credits have been obtained at master's level. Master’s students in their final year are welcome to apply; employment will then be postponed until the master’s degree is
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an advantage. Your degree must correspond to a five-year Norwegian program, where 120 credits have been obtained at master's level. Master’s students in their final year are welcome to apply
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English proficiency by: – proof that the language of instruction of their entire university education (bachelor and master programme) was English, or; – scoring at least 100 on the TOEFL iBT test or 7.5
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of programming (in particular Python) is preferred. Furthermore, the candidate should be highly motivated and willing to work in a team. Good communication skills in both spoken and written English, are a
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requirements for our PhD programme . Skills in Python, C++ or ROS are preferred. How to apply Applications should be submitted via the Robotics and Autonomous Systems PhD programme page. In place of a research