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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description As part of an 18-month prematuration project, your mission will be
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computational fluid dynamics modelling of water treatment and desalination processes is an advantage. Willingness to work within a multidisciplinary group. Demonstrated skills in scientific writing in the form
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circuits, statics, fluid dynamics, engineering physics, manufacturing processes which provides some shop experience, process control and/or instrumentation such as strain gauges, thermocouples, etc
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to delivering exceptional patient care in a dynamic healthcare environment. If you are eager to contribute to a team dedicated to excellence in family medicine, we encourage you to apply. Qualifications: Minimum
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. The PhD candidate will join the team Methods and Algorithms for Bioinformatics (MAB). - Supervision: - Dr Eric Rivals, HdR, (LIRMM), CNRS Research Director in computer science and bioinformatics (web https
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Postdoctoral researcher (M/F). Modeling damage during earthquakes. Comparison with geophysical data.
), an internationally renowned laboratory that combines fieldwork, experimentation, and modeling to advance understanding of geological processes, continental surface dynamics, fracture-fluid interactions, and natural
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. and the Environmental Systems M.S. (Environmental Resources Engineering option and Energy Technology and Policy option). See Department website here: https://engineering.humboldt.edu/ Courses/Areas
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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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National Institute of Research and Development for Electrochemistry and Condensed Matter | Romania | 1 day ago
of materials. • Numerical simulation (CAE) of fluid dynamic behavior using finite element analysis (FEM) and strength criteria. • CAD design (Catia V5, Ansys). Important skills include openness to learning and
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develop computational fluid dynamic (CFD) tools that make exascale computing accessible to a broader set of users. The successful candidate will develop a massively parallel solver, capable of running