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(target journals: International Journal for Numerical Methods in Engineering – IJNME). Deep learning algorithms for high-temperature multiphase problems (target journals: Computer Methods in Applied
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
opportunities for career 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
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(OAE) is a promising method aimed at increasing the ocean's capacity to absorb atmospheric CO₂. However, its biogeochemical, physical, and climatic impacts—as well as its interactions with other
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
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 campus events. UNC-Chapel Hill
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process techniques for the development of ion channel simulation schemes. Design, program and maintain the code necessary for these simulation models. Run numerical simulations. Provide support for
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on: https://www.dges.gov.pt/pt/pagina/reconhecimento Workplan and the objectives to achieve: The workplan proposed comprises two topics, each to be tackled by each studentship offered: Topic 1 - Automatic
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, Process Engineering, Computational Science, or a related discipline Strong foundation in fluid mechanics, gas–liquid two-phase flows, numerical methods (FVM, FEM), and two-phase flow instrumentation
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Missouri University of Science and Technology | Rolla, Missouri | United States | about 18 hours ago
and multidisciplinary student wellbeing team. For department specific information, visit https://wellbeing.mst.edu. Key Responsibilities: Provides individual, group, and crisis counseling with around
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AI. Candidates must possess substantial experience in artificial intelligence and machine learning methods, specifically in AI-driven materials discovery, machine learning applications for materials
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mechanisms using computer simulations and the methods of non-equilibrium statistical physics. The Research The PhD student will work under the supervision of Dr. Philip Bittihn within the European Doctoral