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Field
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across the world. We are looking for motivated researchers to join the HDSC/MDSI Tandem Project "Data science at scale: Training neural models with mixed precision solvers." This is a joint project
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barriers (modelling, experimentation, and monitoring), (ii) Determination of the impacts of subsurface exploitation and usage (induced seismicity, pollutant migration, CO₂ and associated impurities leakage
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, if possible with a focus on modelling/numerical simulations. • A good level of Python programming is required. • A level of scientific English sufficient to conduct research and build international
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ability to fulfil the entry requirements. Prior experience in numerical modelling and groundwater–surface water systems are strongly encouraged. Experience or familiarity with probabilistic modelling
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to qualify (which is 2 years) Highly skilled in numerical modelling and programming is essential Experience with at least two of the following disciplines is expected: o hydrological and/or land surface models
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building models (impervious and with openings) capturing loads and pressures on various structural elements, both horizontally and vertically. Integrating experiments with numerical simulations (e.g. CFD
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teams with colleagues. Your qualifications You are expected to have a Ph.D. in hydrology and have documented experience with numerical integrated hydrological modelling including groundwater, remote
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of Marine Technology at NTNU has a vacancy for a PhD Candidate in Deep Learning enhanced FSI modelling of Multi-modular Floating Structures. The position is part of the AIMOS project (Artificial Intelligence
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Polytechnique de Toulouse (INPT). The PhD student will be part of a group of largely modelling PhD students all trying to make computational fluid dynamics modelling more sustainable in a comprehensive sense
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with a background in fluid mechanics or thermal engineering. Given the scope of the research project, a strong interest in both experimental work and numerical modeling is essential. Familiarity with