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quantum many-body theory with a focus on quantum impurity models (particularly Kondo model). Strong computational skills (with Python or Julia or C++ or Matlab or equivalent) and using numerical techniques
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trips, plus an elective course. Examples of elective courses could include aqueous geochemistry, geomorphology, soils, glaciology, GIS, or numerical modeling. We are seeking candidates who can demonstrate
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Astrophysics, Space Physics, Aerospace Engineering, Applied Physics, or a closely related field. Previous experience with numerical modelling and simulation relevant to space systems of astrophysics and a
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04:59 AM UnitedKingdomTime) Position Description: Apply Position Description One or possibly two postdoctoral positions to work on the theory of generative AI—particularly diffusion models and their
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 12 days ago
-tolerance to the insulin producing beta cells, and 2) Development of immunotherapies for T1D. The work makes use of several genetically manipulated mouse models of T1D, as well as humanized mouse models, and
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complementary data from other Mars missions to strengthen current models and provide comparative insights that enhance research conclusions from Hope observations. Develop Machine Learning methods and run
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excellence of NTU and attracting interest of more industrial collaborators. Key Responsibilities: Develop a new and robust numerical model with lattice Boltzmann method to simulate flow and heat transfer with
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numerous interdisciplinary clinical programs throughout the JDMI enterprise, including at the largest volume cancer centre in the country with >30 clinical colleagues in the Head and Neck Cancer Group. We
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tackling foraging tasks, to work out which algorithm best explains how foragers decide to leave. You will have some experience in computational modelling of behaviour, such as decision-making models
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datasets, modelling approaches, and performance metrics; develop physics-informed and data-efficient machine learning models to predict sorbent behaviour from sparse and multi-modal experimental data; and