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of interpretability methods to ensure ML outputs are meaningful in scientific contexts. Preferred: Background in biomedical data, healthcare, or AI for life sciences. Experience with parallel computing. Familiarity
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ODEs with convergence guarantee and uncertainty quantification,” Mathematics of Computation, Jun. 2025, doi: 10.1090/mcom/4120, https://arxiv.org/abs/2404.19626 C. Offen, S. Ober-Blöbaum, “Learning
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | about 2 months ago
Neural Operators. Your tasks # Design, train and tune surrogate models for electromagnetic field solvers using neural operators # Use symmetries of the modeled plasma physics and numerical methods
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Jan 2026 Is the job funded through the EU Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Versão PT
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abilities Very good knowledge of magnetohydrodynamics, programming and numerical methods. Desirable qualifications, experience and knowledge Experience in stellar evolution theory and models. Desirable skills
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MRI scanners with massively parallel transmit and receive technologies and multinuclear options, a number of DNP hyperpolarizers, and numerous (dozens) of other scanners and instruments placed in
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Engineering, Physics, Applied Mathematics, or related discipline. Proven track record in numerical methods and computational fluid dynamics. Proven track record in machine-learning methods for computational
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Inria, the French national research institute for the digital sciences | Bordeaux, Aquitaine | France | 26 days ago
architecture. More info on the ANR DeepPool project: https://team.inria.fr/mnemosyne/deeppool/ The engineer project will explore one or several of the topics of the ANR project above. The methods developed will
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of scientific computing principles and applications, including numerical methods, simulation techniques, and computational modeling. Proficiency in using version control systems like Git for collaborative
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(multiscale, QSP, PBPK, PK-PD).Apply numerical methods, optimization, and parameter estimation to calibrate models to experimental/clinical data.Perform sensitivity and uncertainty analyses to assess robustness