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Field
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programme of computer science, mathematics, physics, electrical engineering, computational linguistics, or similar with good grades PyTorch skills: experience in training machine learning models with one
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Technomathematics, computer science, engineering, physics, mathematics or natural science or equivalent degree Very good knowledge of techniques and methods of computer-aided sciences Knowledge and experience in
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Physics, Chemistry, Applied Mathematics, or related fields. Desirable: Fluent English, spoken and written Strong background in computational Physics and Statistical Physics Previous work experience in
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of Economic Geology and Mineralogy in the Faculty of Mathematics and Natural Sciences, there is a part-time (66 %) position, subject to the allocation of funds, that is available for next possible appointment
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operating an orbital propellant depot. Requirements: A completed scientific university degree (Master’s or equivalent) in engineering, physics, or technical mathematics with very good grades. Basic technical
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degree in computational engineering, mechanical engineering, computer science, applied mathematics, physics or a similar area very good programming skills in Python good prior experience with neural
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, domain generalization, data-efficient learning, uncertainty estimation, 3D vision. Especially suitable for students with the field of study in computer science, mathematics, engineering, or similar areas
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in teams Good language skills in English Good communication skills Ability to be on-site approx. once per week Especially suitable for students with the field of study in computer science, mathematics
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genetics. With guidance and supervision from both experimental and computational perspectives, this program is ideal for graduates in fields such as molecular biology, biochemistry, mathematics
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models on edge devices Reporting findings and methods in conference and journal papers Your profile Masters, Diploma or equivalent degree in IT/computer science/statistics/applied mathematics/data science