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learning to quantify uncertainty and forecast potential faults. c) Trustworthy Autonomous Recovery: Autonomous self-healing must be verifiable; this challenge is met by designing AI-driven decision engines
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to autonomous systems, robotics, or data-driven modelling. Demonstrable competence in at least one of the key areas related to the position (e.g., autonomous systems, sensor fusion, robot perception, drone
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Massachusetts Institute of Technology, Open Learning Position ID: Massachusetts Institute of Technology-Open Learning-MECHE [#31839] Position Title: Position Type: Postdoctoral Position Location
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within various scientific and engineering disciplines, including ground-based, airborne, and satellite measurements, numerical modelling, and data analysis. The division's goals are to enhance
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to: Complex systems modeling and analysis Digital transformation technologies (e.g., digital twins, IoT, cyber-physical systems) Data- and AI-driven decision-making, analytics, and intelligent systems
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the humanities, social sciences, sciences, and health sciences. The Head of Pollack Library provides strategic leadership for this branch, overseeing a broad range of mission-driven services including research
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100%, Zurich, fixed-term We invite applications for a PhD position on Data-driven and hybrid hydrological modeling co-supervised by Manuela Brunner (ETH Zurich, WSL) and Olivia Martius (University
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100%, Zurich, fixed-term A World-Class Research Environment at the Intersection of Neuroscience and Technology The Neural Control of Movement Lab led by Prof. Dr. Nicole Wenderoth and Brain-Body
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of the Candidate: Completed a PhD in engineering, applied physics, applied mathematics, or a related field. Strong quantitative skills and modeling Advanced coding skills Fluent (oral and writing) in English Enjoys
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candidate will be self-driven, an excellent communicator, have a strong background in digital and model-based engineering in defense or commercial applications. The position will support multiple clients