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. The following links provide further information on diversity and equal opportunities: https://go.fzj.de/equality and and on the targeted promotion of women: https://go.fzj.de/womens-job-journey
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
Bayesian statistics, AI-assisted inverse problems, planetary remote sensing, and environmental monitoring. Where to apply Website https://jobs.inria.fr/public/classic/en/offres/2026-09787 Requirements Skills
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 2 months ago
, as they significantly impact both the performance and accuracy of the overall discretization scheme. Phase 2: learning techniques in wave modeling and inversion To address the inverse problem, we
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Your Job: Digital methods for inverse materials design are essential to efficiently create new, sustainable and recycling-adapted structural metals. Alloys with a reduced number of elements, so
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. Hu, X. Wei, X. Wu, J. Sun, J. Chen, Y. Huang, J. Chen, A deep learning-enhanced framework for multiphysics joint inversion, Geophysics, 88(1), K13-K26, 2023. https://doi.org/10.1190/geo2021-0589.1 [3
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/1312.6114 . [5] X. Meng and G. E. Karniadakis, A composite neural network that learns from multi-fidelity data: Application to function approximation and inverse PDE problems, JCP, 401, 109020 (2020). [6] M
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Website for additional job details https://emploi.cnrs.fr/Offres/Doctorant/UMR5295-MATMAL-001/Default.aspx Work Location(s) Number of offers available1Company/InstituteInstitut de mécanique et
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: https://metatune.webs.upv.es/jobs/ (you can also find it at the end of the job description). Where to apply Website https://metatune.webs.upv.es/jobs/ Requirements Research FieldPhysicsEducation
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Additional Information Website for additional job details https://www.academictransfer.com/359563/ Work Location(s) Number of offers available1Company/InstituteUvACountryNetherlandsCityAmsterdamPostal
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these challenges by advancing sensitivity-based modelling, fluid–structure interaction (FSI) methods, inverse problem solving, and surrogate modeling techniques, ultimately enabling predictive, adaptive, and