360 computer-science-intern-"https:"-"https:"-"https:"-"https:"-"U.S" positions in Switzerland
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close collaboration with experimental and clinical partners, and we are embedded in one of the strongest AI and computer science environments worldwide. Learn more about our research and recent work
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develop predictive tools for mechanical failure. Our team is highly interdisciplinary and international, bringing together researchers with backgrounds in materials science, mechanics, and applied physics
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will be enrolled in the electrical engineering doctoral program at ETH Zurich. The project is embedded in the National Competence Center for Research Muoniverse and funded by the Swiss National Science
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. ENDOTRAIN will train a new generation of interdisciplinary experts who merge clinical endocrinology, artificial intelligence, data science, engineering, ethics and law into an integrated field of digital
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their recruitment date. The student will be enrolled in the structured PhD programme of the Department of Mechanical and Process Engineering or the Department of Health Sciences and Technology
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The Chair of Strategic Management and Innovation provides an inspiring, team-based research environment with a dynamic and international group of researchers. Our team has a strong track record of
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for mechanical failure. Our team is highly interdisciplinary and international, bringing together researchers with backgrounds in materials science, mechanics, and applied physics. We work across a broad range of
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of research grants and writing of scientific publications Supervision of students and interns Collaborate closely with chemists, materials scientists, and electrochemists. Your profile PhD in chemistry (or a
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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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policy, political economy, economics, sociology, computational social sciences, or a related field Strong knowledge of advanced quantitative methods is essential (e.g., econometrics, causal inference