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models. The scientist will conduct research using machine learning and classical parameterization methods on data from ocean gliders equipped with microstructure turbulence sensors, turbulence resolving
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aircraft, utilized for research into thermal management and system health monitoring, supporting studies in military aircraft systems. Engaging with these facilities allows students to acquire practical
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students pursue their Ph.D. in a similar area, which plenty of opportunity to collaborate and learn from and with peers. About the research project This ad is for a Ph.D. student researcher that will work in
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affect surface outcomes, benchmark against conventional techniques, and evaluate performance of the finished components. You’ll also delve into intelligent automation and machine learning to optimise
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(Kingdom of the) [map ] Appl Deadline: 2025/06/30 11:59PM (posted 2025/06/11, listed until 2025/12/11) Position Description: Position Description Joint-PhD Position on Advancing Machine Learning Methods
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algebraic geometry, or representation theory; familiarity with programming and the use of computer algebra. Our offer A position for 18 months, with an extension to a total of four years upon successful
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-driven energy systems research – scalable, transparent, and interoperable. Your tasks in detail: Development of a structured description format for the unambiguous and machine-readable characterization
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projects Designing for complex or high-consequence systems Human-centred product, service, or interaction design in healthcare, defence, or critical infrastructure Applied human-computer interaction or
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. The position is placed in the Division for Computer Networks and Systems and is formally employed by Chalmers University of Technology. Our research spans from theoretical computer science to applied systems
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We are seeking a highly creative and motivated Postdoctoral Research Assistant/Associate to join the Machine Learning Group in the Department of Engineering, University of Cambridge, UK. This