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/Qualifications - Automation or applied mathematics background, with a strong interest in physical models and numerical method - Analysis of partial differential equations, variational approach, Bayesian estimation
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discovering research and potentially pursuing a PhD. Expected skills • Solid background in numerical methods (PDEs, finite elements, scientific computing). • Interest in modeling, model order reduction, and
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of territories, etc.). Modelling Urban Territorial Transformations of the Baltic Region: A Spatio-Temporal Computational Approach. (What is an Integrating Mathematics, Remote Sensing, and Geo-AI Simulation?) In
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the following ones. Exploration of active auditing techniques for large machine learning models, use of reinforcement learning, potential application to recommender systems. The PhD will mainly investigate
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your arrival. The EM2C laboratory is seeking a highly motivated candidate for a PhD in data-driven, physics-informed, and probabilistic modeling of turbulent combustion. The PhD work will combine
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simulations, optimisation, machine learning and turbulence modeling. The researcher must hold a Phd in fluid mechanics / Applied mathematic / Machine Learning. Website for additional job details https
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4 fully funded PhD student positions in the computational, mathematical & experimental plant science
. They apply and develop a broad range of interdisciplinary technologies ranging from genetics and genomics to structural biochemistry, advanced imaging and computational and mathematical modelling in various
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14 Nov 2025 Job Information Organisation/Company IMT Atlantique Research Field Computer science Mathematics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country France
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Inria, the French national research institute for the digital sciences | Toulouse, Midi Pyrenees | France | 14 days ago
-Stokes, RANS and ZDES model equations. The objective of this PhD is to develop adaptive techniques compatible with high order boundary approximations. The aim is to be able to efficiently reduce the error
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of environmental seismology, an emerging field focused on interpreting seismic signals generated by surface processes. This interdisciplinary PhD project aims to integrate hydraulic measurements, physical models and