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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 12 days 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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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The researcher will work on some inverse problems in
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with advanced statistical techniques (optimal Bayesian, Markov Chain-Monte Carlo, etc.) to solve the forward and inverse problems involved. Additional information about AGAGE, CS3, and MIT atmospheric chemistry
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PhD project involves interdisciplinary research at the interface of computer science and mathematics and addresses a complex, coupled inverse problem with explicit uncertainty quantification. Research
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 28 days 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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discrete-time systems. In particular, we are looking for a strong candidate that want to work with developing computationally feasible methods for such inverse problems; methods that also comes with
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. The PDRA will quantify the differences in calculated and measured experimental conditions by adapting the Geodetic Bayesian Inversion Software ( https://doi.org/10.1029/2018GC007585) ). Working alongside our
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27 Jan 2026 Job Information Organisation/Company LINGNAN UNIVERSITY Research Field Computer science Physics Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Application
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. Scientific Missions and Objectives The doctoral researcher will focus on the inverse problem of reconstructing solid motion and flow states from distributed sensor data, with emphasis on physics-informed
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-stationary configurations [2]. Reconstructing the acoustic field from near-field measurements constitutes an inverse problem, which has been extensively studied using various regularization strategies