31 application-programming-android-"Prof" Postdoctoral positions at Massachusetts Institute of Technology in United States
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visits to our partner lab in Vienna. Applicants must have a Ph.D. in physics or a related field by the start of the position. Applicants should have a strong background in experimental laboratory-based
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/supporting applications development and experiment realizations on DIII-D and international tokamaks; support the creation and validation of machine learning models, particularly in areas like plasma
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; general knowledge of fusion-grade plasma physics; strong experimental, analytical, and programming skills; and ability to work collaboratively in a team-oriented research environment. PREFERRED: Hands
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for metallic wall tokamaks; work in the Disruptions group and focus on the application and controllability quantification of real-time solutions for avoiding and preventing off-normal events, e.g. tearing and
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Posting Description POSTDOCTORAL ASSOCIATE, Plasma Science and Fusion Center (PSFC), to join a team to conduct research in support of the newly awarded Army Research Office sponsored Program to
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 2 months ago
/supporting applications development and experiment realizations on DIII-D and international tokamaks; support the creation and validation of machine learning models, particularly in areas like plasma
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for Information and Decision Systems (LIDS) and the MIT Sloan School of Management in collaboration with The Social and Ethical Responsibilities of Computing (SERC) invite applications for a postdoctoral associate
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Subpolar Gyre (SPG) as part of the POLEMIX program, funded by the Forecasting Tipping Points initiative. This role involves integrating autonomous profiling observations with the ECCO (Estimating
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. The full job description is available here. https://www.dropbox.com/scl/fi/pei7s6ncbj1ygcwsya2q0/Postdoc-2026_2027-call-for-applications-8.28.25.pdf?rlkey=tf4zawqnes5ulx7gwrp5218bu&e=1&st=hwztd7q6&dl=0 Job
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application of scenario optimization techniques that could be applied in between shots and between run days, to include model correction techniques and transfer learning to maximize success probability of SPARC