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Your Job Develop a reinforcement learning (RL) controller for a liquid–liquid gravity settler, trained entirely offline in a simulated environment Use existing physics-informed neural network (PINN
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University of California, San Diego | Estancia de San Diego, Guanajuato | Mexico | about 5 hours ago
degree in ocean, earth or atmospheric sciences, mathematics, physics, chemistry, biology, environmental policy or a related field. Additional qualifications (required at time of start) Candidates are
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include teaching or other departmental duties, up to a maximum of 20% of full-time. Your qualifications You have graduated at Master’s level in Chemistry, (Applied) Physics, Materials Science, or a
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Faculty Positions in AI for Theoretical and Physics-Informed Modelling (Full Rank) Employer XIAN JIAOTONG LIVERPOOL UNIVERSITY (XJTLU) Location Suzhou, China Salary Competitive salary in the market
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Übersicht PhD position for developing multi-physics models of planar inductors and transformers 100%, Zurich, fixed-term Drucken The Laboratory for High Power Electronic Systems (HPE) at the
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Simons Collaboration on the Physics of Learning and Neural Computation | California City, California | United States | about 11 hours ago
Position Description The Simons Collaboration on the Physics of Learning and Neural Computation is searching for postdoctoral fellows at Stanford to perform scientific research on AI, working in the
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chemistry, chemical engineering, materials science, physics, or a closely related scientific discipline relevant to the Chemical Sciences Division mission. A minimum of ten years of progressively
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Wissenschaften Impact and Planetary Physics, SFB 1759 Research assistant (postdoc) (f/m/d) full-time job limited till 30.06.2030 salary grade (Entgeltgruppe) 13 TV-L FU reference code: SFB1759-B03-KW
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. Learn more about NTU College of Engineering: https://www.ntu.edu.sg/engineering Nanyang Technological University, Singapore: https://www.ntu.edu.sg/ Share this job Facebook Twitter LinkedIn Apply now