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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
growth, skill development and lifelong learning and enjoy exclusive perks for numerous retail, restaurant and performing arts discounts, savings on local child care centers and special rates on select
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Numerical relativity, machine learning Where to apply
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date); Good knowledge of analytical methods and/or numerical simulations; Very good command of English, both written and spoken. Essential skills and abilities Experience in machine learning; A strong
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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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Functional Theory (DFT) Familiarity with artificial intelligence methods Good knowledge of electronic structure methods Experience with Linux, Git and related tools Knowledge in the field of high-performance
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density functional to ab initio methods coupled to effective field theory) and related numerical and formal techniques. We are particularly fond of interdisciplinary connections and emerging technologies
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for geometric PDEs, in particular for fluid problems posed on surfaces. Both theoretical analysis of numerical methods and code development. Job requirements: PhD in mathematics or applied mathematics, experience
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 15 days ago
investigations focused on spin dynamics, · Perform numerical simulations to study: - ultrafast magnetization phenomena, - interactions with surface acoustic waves, - propagation of sound waves in the presence of a
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requirements and focusing on data-value maximisation. This project will utilise innovative machine learning methods and tools from process systems engineering to simultaneously optimise product quality and the
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Ordinance nr. 33/2019, of January, 25th. It is mandatory to present the certificate to sign the contract. More information is available on: https://www.dges.gov.pt/pt/pagina/reconhecimento Workplan and the