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of reactions between the metal-bearing hydrothermal fluid and organic carbon. The task will implement an innovative methodology integrating in-situ spectroscopy and physicochemical modeling. Through
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of the Research Institute, New York University Abu Dhabi, seeks to recruit a Post-Doctoral Associate to work in the fluid mechanics laboratory for experimental fluid dynamics. SITE is inviting
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in September 2026. Job requirements You hold a PhD with a focus on experimental fluid mechanics, for example in aerospace engineering, mechanical engineering, or applied physics. You have proven
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of supporting the selection of aortic valve prosthesis using CFD simulation, machine learning and multi-stage validation, (2024/54/E/ST8/00100) Requirements: PhD in technical sciencesThe mandatory formal
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); - Experience with data balancing techniques; - Desirable basic knowledge of Multiple Input, Multiple Output (MIMO), Fluid Antenna System (FAS), and Compressive Sensing (CS); - PhD degree obtained within the last
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, candidates with prior experience in theoretical physics, fluid mechanics, kinetic theory, dispersive equations or harmonic analysis will be given special attention. The Postdoctoral Associates will be
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 4 hours ago
and aerodynamics through the use of comprehensive analysis, high-order computational fluid dynamics (CFD), and direct numerical simulation (DNS) tools. The postdoctoral researcher will work with CAMRAD
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to join an active and collaborative research group led by Associate Professor Palin in the Department of Earth Sciences at the University of Oxford. The group focuses on fluid–melt–rock interactions across
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Palin in the Department of Earth Sciences at the University of Oxford. The group focuses on fluid–melt–rock interactions across a range of metamorphic and geodynamic settings, including Early Earth
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Max Planck Institute for Solar System Research, Göttingen | Gottingen, Niedersachsen | Germany | 21 days ago
qualification PhD in fluid dynamics, physics, applied mathematics, computer science, or a related field. Experience with machine learning, numerical methods for PDEs, TensorFlow or PyTorch, and Python. Experience