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hydrodynamic and CFD simulations. Coordinate procurement and liaison with vendors/suppliers. Work independently, as well as within a team, to ensure proper operation and maintenance of equipment. Job
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initiatives is highly desirable. Experience with computational tools (e.g., CFD, FEA, system-level modeling) and/or experimental platforms for energy systems is expected. Position # 2 - Machine Learning and AI
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will be the Head of Department. About the project The successful candidate will be part of the project SAPPHIRE (https://sapphire.norceresearch.no/ ). SAPPHIRE aims to contribute to cleaner and more
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changes), Computer Science and Informatics (Numerical Analysis; simulation, optimization and modelling tools; Computational Fluid Dynamics (CFD)), Product and Processes Engineering (Space Engineering
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Number AE2025-0514 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0514.pdf CALL FOR GRANT
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modeling and numerical methods Experience with multiphase flow modeling (e.g., TFM, CFD-DEM, DNS, LBM) Solid programming skills Experience working in Linux/HPC environments Ability to conduct independent
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, applied mathematics, or a closely related field. Strong background in computational modeling and numerical methods Experience with multiphase flow modeling (e.g., TFM, CFD-DEM, DNS, LBM) Solid programming
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unrealistic for simulating a pilot-scale or industrial mixer with real powders [1]. Therefore, more macroscopic models need to be developed. CFD-type simulation methods [2] might be developed to that purpose
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designing against diffuse pollution. Typically, these processes are studied by laboratory experiments and/or computational fluid dynamics (CFD) approaches, often limited to an idealised patch of stems where a
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deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian You will be part of a dynamic research team working on topics relevant