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Technical College, Kasitsna Bay Campus, Seward Marine Center, Tok Campus, Kuskokwim Campus, and Northwest Campus) Online: https://www.uaf.edu/orca/files/ASFSR.pdf . Request a paper copy in person: UAF Office
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Technical College, Kasitsna Bay Campus, Seward Marine Center, Tok Campus, Kuskokwim Campus, and Northwest Campus) Online: https://www.uaf.edu/orca/files/ASFSR.pdf . Request a paper copy in person: UAF Office
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, Community and Technical College, Kasitsna Bay Campus, Seward Marine Center, Tok Campus, Kuskokwim Campus, and Northwest Campus) Online: https://www.uaf.edu/orca/files/ASFSR.pdf . Request a paper copy in
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research tasks: (i) modeling electric and magnetic excitations in two-dimensional (2D) materials, and (ii) simulation of charge transport phenomena in plasmonic crystals with 2D electron gas layers, with
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be embedded within Moderna's Clinical and Quantitative Pharmacology (CQP) function and will contribute to key modeling and simulation deliverables for drug candidates across early and late stages
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research tasks: (i) modeling electric and magnetic excitations in two-dimensional (2D) materials, and (ii) simulation of charge transport phenomena in plasmonic crystals with 2D electron gas layers, with
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the development of compact device modeling, SPICE simulation and with programming skills in general programs such as python, Matlab or similar. Experience on memristors is also acknowledged. Experience in circuit
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of industrial processes. In a joint effort of both institutes, the Department AI4Quantum – Machine Learning for Quantum Simulation and Computing and Thermal Energy and Process Engineering are looking for a PhD
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facteurs abiotiques, mécanismes d'adaptation…) qui peuvent confondre les résultats et aboutir à des faux positifs en termes de marqueur de stress biochimique. Une façon de contourner cette limite serait de
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 4 hours ago
assimilation Integration (JEDI) framework for atmospheric data assimilation Develop machine learning foundation models based on simulated observations from high fidelity atmospheric simulations for developing