179 computer-science-intern-"https:"-"https:"-"https:"-"https:"-"UCL"-"UCL"-"UCL" positions at ETH Zurich
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, Switzerland [map ] Subject Areas: Computer Science / Distributed Systems and Networking , Networking , Networking and distributed systems Appl Deadline: 2026/01/08 11:59PM (posted 2025/11/10, listed until
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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
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fields, and Gaussian Splatting). Profile Degree in Computer Science or a related field, with several years of professional experience as a software engineer Strong proficiency in Python and C#, and
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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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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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researchers across architecture, robotics, computer science, and engineering An engaged international community of researchers and educators Professional development and networking opportunities through
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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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Physics or Engineering with a specialization in precision instrumentation. Workplace Workplace We offer This position offers a unique bridge between high-level academic research at ETH Zurich and the fast
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, engineering, physics, or a related field, and with strong interest in the cryosphere. The successful candidate has experience in computational data analysis or numerical modelling. You are eager to work
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-phonon coupling elements. With these, dedicated scattering rates can be computed and then used in quantum transport simulations. Down the line, we aim to pre-train a common GNN backbone model capable