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Field
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background relevant to the multidisciplinary research of our IMPRS-ML Faculty , including but not limited to Biology, Biochemistry, Biophysics, Chemistry, Computer Sciences, Engineering, Mathematics, and
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presentation and publication of the results Requirements: university degree (Master's or equivalent) in geodesy or a related subject (geophysics, geoinformatics, physics, mathematics) excellent analytical skills
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considered to be self-funded students for the purposes of admission. Applicants should have (or expect to obtain by the start date) at least a first class degree in an Physics, Mathematics, Electrical
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master's degree in agricultural or environmental economics, applied mathematics, or a related field Good background in bio-economic modelling, CGE modelling, and optimization techniques Experience with
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., Computer Science, Environmental Engineering, Electrical Engineering, Physics, Applied Mathematics, or a related area). • Strong interest in applying AI to environmental challenges. • Good communication
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towards science literacy and STEAM (Science Technology Engineering Arts Mathematics) education. The network’s focus: Exploratory behavior is at the core of what it means to be human. Being confronted with
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science, mathematical modelling, data science, transport behaviour, or related fields? Then this PhD position might be the right for you. Ensuring sustainable mobility in dense urban areas is a big challenge faced by
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the laser heat flux on tape and substrate. Couple the two models and validate the result on an industrially relevant part. We are looking for a colleague who has a very strong background in mathematical
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within the University. We offer first-rate education and research in a wide range of science and engineering disciplines, from classical disciplines such as mathematics, astronomy and mechanical
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scholarship is suitable for students with a background in Engineering, Mathematics, and Computer Science. Students with interests in machine learning, deep learning, AI, intelligent decision making