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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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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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. 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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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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, Geotechnics, Computational Mechanics, or a related discipline. You have a solid background in fluid mechanics, soil mechanics, and numerical methods. Experience with SPH methods, FEA, or DEM
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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
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Offer Starting Date 1 Nov 2025 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number BAP-2025-579 Is the Job related to staff position within a
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Application Deadline 9 Oct 2025 - 23:59 (UTC) Type of Contract Temporary Job Status Full-time Offer Starting Date 20 Oct 2025 Is the job funded through the EU Research Framework Programme? Not funded by a EU
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have a broad experience with a wide range of methods in cognitive and computational neuroscience, including specifically functional magnetic resonance imaging, electroencephalography, multivariate brain
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18 Oct 2025 Job Information Organisation/Company KU LEUVEN Department Associated Faculty of the Arts KU Leuven Research Field Arts » Visual arts Computer science » Systems design Researcher Profile