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(Grafana) and remote experimentation APIs to give researchers live insight into grid behavior and improve user experiences on our platform. Profile You are an ETH student enrolled in Computer
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wet-lab scientists and translating their needs into analysis Academic degree in any of the relevant areas, including (but not limited to) computer science, statistics, or biology A master’s degree in
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world-class research and teaching ranging from integrated circuits to computer networks, from wireless communications to signal processing, and from control theory to electric energy. It offers a
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from 1 Dec 2026 (flexible start date). Funding is provided for up to four years. Applicants should hold an MSc degree and have a strong background in computer science, engineering, mathematics, physics
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discipline You should have a strong motivation to build a quantum computer from scratch Excellent spoken and written English Willingness to work in an international and diverse team Experience in any of the
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reliability Citation quality and evidence grounding Calibration, uncertainty, and appropriate deferral Trace auditability and clinician-in-the-loop evaluation Profile Must Have PhD in Computer Science
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benchmarks Debug common post-training issues, including optimisation instability, reward hacking, regressions, and evaluation failures Profile Essential MSc or PhD in Computer Science, Data Science
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interest in developing new approaches at the intersection of fluid dynamics and quantum computing. In particular: You hold a PhD in computational fluid dynamics, applied mathematics, physics, computer
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2027) in a relevant field (e.g., architecture, civil, computer science, mechanical engineering, material science, etc.). Strong fit to Design++ scope and impact goals. Nice-to-haves Evidence of
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. Specifically, we are looking for someone with: A Master’s or PhD degree in computer science , machine learning, geo-informatics, engineering, remote sensing or a related field Several years of