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strong programming, modelling and data analysis skills in Python and/or R. Experience with the formulation and implementation of mathematical optimization problems can give you a competitive edge. The
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conferences.Requirements:- Passion about working at the intersection of mechanics and machine learning.- Bachelor/Master’s degree in Civil Engineering, Mechanical Engineering, Applied Mathematics, Computational Science or
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. Experience with the formulation and implementation of mathematical optimization problems can give you a competitive edge. The candidate should have excellent written and oral communication skills in English
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the intersection of mechanics and machine learning. - Bachelor/Master’s degree in Civil Engineering, Mechanical Engineering, Applied Mathematics, Computational Science or related areas. - Background in computational
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range of research groups and institutes across different faculties. The position is offered in the Department of Mathematics and Computer Science. About IBM Research - Zurich: The IBM Research Laboratory
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be carried out in collaboration with groups in theoretical chemistry, computer science and applied mathematics. Job description As a PhD student in our growing team, you will perform quantum-chemical
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, mathematics, sustainable development or related disciplines, be fluent in English, and be interested in pursuing an academic career. They should be willing to collaborate with members of the research team in
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in machine learning, seismic monitoring and earthquake seismology. The ideal candidate should: A Master’s degree in Earth Sciences / Physics / Mathematics / Computer Sciences or a related discipline is
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of Prof. Isabelle Marthot-Santaniello (Department of Ancient Civilizations) and of Prof. Ivan Dokmanić (Department of Mathematics and Computer Science ) with support from the Center for Data Analytics (CeDA
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Earth Sciences / Physics / Mathematics / Computer Sciences or a related discipline is required. Applicants must have obtained their Master's degree by September 2024 A strong foundation in analyzing large