48 computer-programmer-"https:"-"Prof"-"https:"-"https:"-"https:"-"https:"-"https:"-"Dr"-"UCL" positions at ETH Zurich
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research at the forefront of computer science. Successful candidates should establish and lead a strong research program. The new professor will be expected to supervise doctoral students and teach both
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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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for the physically informed processing and joint analysis of time-series data. The successful candidate will conduct observational programmes with the SPECULOOS facility and actively participate in the scientific
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2026, with a 100% workload, based in Zurich, and is fixed-term for three and a half years. Working across sociocultural, political-economic, and theoretical contexts, the LUS Doctoral Program fosters
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networks Publish results in peer-reviewed journals and present at scientific conferences Co-supervise MSc, BSc, and PhD students and contribute to teaching in the Forest and Landscape Management program
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psychologists, neuroscientists, computer scientists, clinicians, and data scientists across the Singapore-ETH Centre (SEC), the National University of Singapore (NUS), and Nanyang Technological University (NTU
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, neuroscientists, computer scientists, clinicians, and data scientists across the Singapore-ETH Centre (SEC), the National University of Singapore (NUS), and Nanyang Technological University (NTU), the PhD student
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Each doctoral student will lead a coherent subproject within this broader research program: Position 1: AI for Computational Thinking Focuses on designing and studying AI-assisted programming
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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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scientific publication. Source Data extraction from PDF documents to compile metadata of projects funded under ETH Board Open Research Data (ORD) program Contribute to data packages generated by openwashdata