8 two-phase-flow Fellowship positions at King Abdullah University of Science and Technology
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looking for postdoctoral researchers in the area of computer vision, AI, and machine learning. The initial appointment will be for 2 years with a possible extension with a tentative start date in January
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fractures can play a key role on production performance. One of the persisting challenges is to create complex 3D fracture networks and solve multiphase flow efficiently. None of the existing tools can
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and algorithms for efficient learning of dynamical models of micro-states evolving over time including machine based learning of derivation of coarse grained representations; (ii) implementation
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capacity in deep aquifers, depleted hydrocarbon reservoirs, and others. A database for the current CO2 stationary sources with locations, rates and industry sector will be used. The project may also include
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funded for 2-3 years with a competitive salary and benefits. For more information about living and working at KAUST, please refer to the University website: https://www.kaust.edu.sa/en/live About KAUST
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flow batteries: aqueous organic and other emerging systems Membrane-electrode assemblies (MEAs) for fuel cells and electrolyzers Responsibilities Lead one of the above-mentioned research directions and
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for chemical and morphological characterization. The candidate should preferentially have a PhD in chemistry, polymer science, or membrane preparation and characterization. Besides the salary (contract of 2
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, programming, and connecting accelerators to enhance performance, latency, and efficiency in emerging applications. Our current projects are exploring hardware acceleration in smart NICs, application-specific