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Requisition Id 16949 Overview: We are seeking a Postdoctoral Research Associate who will focus on efforts related to gas dynamics, fluid flow, and mass transfer. This position resides in the Applied
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support the optimization of hydrogen storage systems. · PhD in fluid mechanics, energy engineering, chemical/process engineering, or related field · Strong background in Computational Fluid Dynamics (CFD
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postdoctoral position lies at the interface of fluid mechanics, phase-change physics, and industrial application. It is part of ARCNL’s Source Department and the EUV Plasma Processes group. We investigate
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. · Location: CEA LITEN – INES Site, Le Bourget-du-Lac, France You should hold a PhD in Energy Engineering, Mechanical Engineering, Thermodynamics, Fluid Mechanics, Process Engineering, or a related field. We
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 1 month ago
involving complex fluids that interact with gases, other fluids, or solids. The role also includes examining how these systems respond to perturbations in material properties and environmental conditions. The
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Full time: 35 hours per week Fixed term: for 36 months Posts available: 2 The Opportunity: This project aims to (1) understand the fluid dynamics of small-scale processes in the Arctic Ocean that
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(laser, X-rays, electrons, ions, etc.). It accounts for the hydrodynamic evolution of fluid or solid materials (including mechanical effects), energy deposition of different types, thermal conduction
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. The work combines physics-based thermal design and process-level system simulation with high-fidelity computational fluid dynamics and fast reduced-order and machine-learning models, so that the final design
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will have a strong background in research processes, including report writing, and producing high-quality publications, with experience in cardiovascular modelling, fluid–structure interaction or high
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through data-driven modeling and optimization. The successful candidate will work at the intersection of thermal-fluid sciences, control theory, and artificial intelligence/machine learning to advance