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validation of the numerical model. Candidates should be holding a MSc degree in Engineering (or equivalent), with demonstrated experience in computational fluid dynamics (CFD), preferably in hydraulic
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inverse problems. The team aims at developing Bayesian computational methods for such (ill-posed) inverse problems and aims both at increasing their validity and at reducing their computational cost. In
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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of computational chemistry Position You work actively You work actively on the preparation and defense of a PhD thesis in the field of Computational Chemistry in the research group MOSAIC within the Department
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, Coastal Engineering, Mechanical Engineering, Hydraulics, Geosciences, or a related field Strong background in hydrodynamics, sediment transport, and numerical modeling Experience with computational tools
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scan speed. In parallel, the fabrication of composition-graded structures requires combined control of laser power, scan speed and powder feed ratios, continuously responding to the changing process
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. the light curves and spectra) of these stars analytically and through numerical methods, based on binary stellar evolution models. You will also investigate potential observable signatures of binary evolution
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the necessary theoretical support. Practical implementation of the developed methods is part of the project, and hence skills in computations and implementation (via codes written in open source software, such as
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Offer Starting Date 9 Mar 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number BAP-2025-697 Is the Job related to staff position within a
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- 23:59 (UTC) Type of Contract To be defined Job Status Full-time Offer Starting Date 12 Jan 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference