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complete) a PhD in Physics/Astrophysics with focus on data analysis, preferably of gravitational waves data · You have experience and in-depth understanding of machine learning methods for data
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aims at developing a new and innovative system for the large scale analysis of stellar spectroscopic data. The "CHEmical Survey analysis System" (CHESS) will combine machine learning ideas with
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on topics including molecular clouds and star formation. Candidates with experience in machine-learning and magnetic field observation/simulation are particularly welcome to apply. Experiences with (sub-)mm
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QCD data from the STAR experiment. We have recently collected significant data sets with polarized high-energy proton collisions and expect to continue to collect more in the RHIC Run-24 with a wide
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applications in these fields. You are also expected to contribute to the teaching programme of the mathematics department. What do we require? a PhD in mathematics; a strong scientific expertise in complex
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have the opportunity to engage through our ten employee resource groups, numerous employee-driven clubs, and learning and professional development classes. NREL supports inclusive, diverse, and unbiased
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supportive, inclusive, and flexible work environment, you’ll have the opportunity to engage through our eight employee resource groups, numerous employee-driven clubs, and learning and professional development
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condensers Support integrated multi-physics simulations of reactor core, and other system components Develop reduced-order calibration approaches and apply machine learning and Bayesian calibration methods