375 computer-science-intern-"https:"-"https:"-"https:"-"https:"-"IFM" positions in Switzerland
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100%, Zurich, fixed-term The Clinical Genomics team led by Dr. André Kahles at the Biomedical Informatics Lab (BMI Lab), headed by Prof. Gunnar Rätsch, at ETH Zurich, is seeking a highly motivated
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that will shape your research career. Your profile We are looking for 2 highly motivated PhD students with a strong analytical background and an MSc degree in Physics, Computational Chemistry, Materials
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well as metabolic, neurodegenerative, autoimmune, and infectious diseases. Job description Postdoctoral projects will combine catalyst engineering, computational simulation, bioelectrode device fabrication, and
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well as metabolic, neurodegenerative, autoimmune, and infectious diseases. Job description PhD projects will combine catalyst engineering, computational simulation, bioelectrode device fabrication, and electrical
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on field and analytical feedback. Authoring and co‑authoring peer‑reviewed scientific publications and presenting results at international conferences. Profile PhD in Environmental Science, Environmental
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100%, Zurich, fixed-term The upcoming Molecular Engineering Thermodynamics (MET) Group at ETH Zürich is looking for a doctoral student to develop and improve computational tools for the molecular
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day. You will collaborate mainly with your colleagues from Facility Management, internal IT Services, Events and Communications, and the Human Resources team. In this function, your responsibilities
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100%, Zurich, fixed-term The Programming, Education, and Computer-Human Interaction group in the Department of Computer Science is recruiting one research intern to work broadly in the area of
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80%-100%, Zurich, fixed-term The Swiss National Supercomputing Centre (CSCS) develops and operates a high-performance computing and data research infrastructure that supports world-class science in
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datasets The position is limited to two years. Profile University degree (MSc or PhD) in data science, computer science, physics or a related field Experience in training and validating large-scale deep