1,368 structural-engineering "https:" "https:" "https:" "https:" "UCL" "UCL" positions at Nature Careers
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difficult to capture with compact classical models [3, 4]. However, even when a quantum model shows promise, running it as a production inference engine is often impractical in robotic systems. Knowledge
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activities to promote SnT's research and citizen science initiatives Your profile... A Master's degree in Electrical Engineering, Computer Science, Applied Mathematics, or a related fieldA strong background in
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profile PhD in Electrical Engineering, Computer Science, Applied Mathematics, or a closely related fieldStrong research track record, preferably with publications in leading AI and Computer Vision
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$50,852.80 (minimum) - $63,566.00 (midpoint) - $82,635.80 (maximum) Please note: this range is pro-rated for part-time, 20 hours per week. Pay Type: Annual HHMI’s salary structure is developed based
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. #LI-BG1 Compensation Range $18.00 (minimum) - $24.90 (maximum) Pay Type: Hourly HHMI’s salary structure is developed based on relevant job market data. HHMI considers a candidate's education, previous
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structures or animal behaviors. The PTR-Bioimage Analysis team within Project Technical Resources (PTR) collaborates with the AI@HHMI initiative, Team Projects, and Janelia laboratories to provide ground
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the MPG. You will lead a high-performing team in a world-class international environment, supported by in-house engineering, high-performance computing, and the services provided by the Max Planck Society
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, immersive learning environment, and interdisciplinary collaboration across the natural and social sciences, engineering, and policy. DUML fosters a close-knit, hands-on academic community and offers
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Ability to work in a team Desirable qualifications are: Teaching experience / experience of working with e-learning Knowledge of university processes and structures Basic experience in academic research
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skills We are looking for a candidate with a PhD in physics, mechanical engineering, or applied mathematics. We expect a strong background in dynamical systems, reinforcement learning, and optimization