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candidate with a PhD degree in computer science, physical chemistry, chemical physics, theoretical physics, or a related field, with a strong background in training GNN-based ML predictive models (Equiformer
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leading journals and conferences. About you · a PhD in Materials Science and Engineering, Physics, Materials Characterisation, Computational Materials Science, or a closely related discipline
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collaboration with the Department of Advanced Computer Science and the Sensor Engineering group, creating a highly interdisciplinary research environment at the intersection of plant science, engineering, and
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Candidates must have a PhD in physics or mathematics and research experience in one or more of the following:: cosmology, gravity, or quantum field theory. Experience in cosmology and scientific programming
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technical problem solving. Work collaboratively with the CI, PIs, research staff, PhD candidates, Honours students and external project partners. Assist the CI and PIs with the technical supervision and
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across Europe. Your profile We are looking for a self-motivated team player ready to work independently in Empa's vibrant international research environment. The ideal candidate holds a PhD in materials
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writing Experience of working collaboratively in large, diverse teams PhD, or equivalent professional experience relevant to the role
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partners. Who we are looking for The following requirements are mandatory: A doctoral degree in mechanical engineering, mathematics, physics, computer science, or a relevant field of fluid or structural
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Associate must hold an MD or MD/PhD degree with clinical research experience, or a PhD degree in biomedical engineering, medical physics, computational science, or a related field with experience in vascular
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the pragmatism that is needed to move a project forward. By the time the position starts, you have obtained a PhD degree in Data Sciences, Computer Sciences, Physics, Earth Sciences, Civil Engineering, or a