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solution. S2) Pre-existing fracture network/faults, having gas-entry pressure lower than the scCO 2 pressure and intrinsic permeability higher than that of the surrounding clay-rich rock (typically two order
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | about 1 month ago
algorithms for real robots that use language models and foundation models. Write papers and present them at conferences. Write, test, validate and document its associated software. Experiments with real robots
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for the turbomachinery design optimization process conducted by a parallel PhD student at LMFA. The numerical solver involved is ProLB. It is an innovative Computational Fluid Dynamics (CFD) software solution developed
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data scientists, software engineers, biomedical researchers, and clinicians. Your research will focus on developing AI- and LLM-enabled methods and tools to structure, harmonise, and analyse clinical
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adaptive mesh refinement for better resolution in key areas like heat transfer and flame chemistry. Reduced NH3/H2 mechanisms will be used for combustion chemistry, conjugate heat transfer (CHT) and
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analysis) to compare brain responses with predictions of computational models (deep neural networks developed by the NASCE team). The objectives include assessing how the brain segments, groups
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of software to validate the integrity and durability of a nuclear power plant containment structure, based on a multiphysics-multiscale approach and data to build a digital twin. • Participate in consortium
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institutions, Luxembourg's leading international financial centre and its vibrant business community. Institutional and private sector partnerships, sponsored Chairs and a growing network of international
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. Familiarity with single-cell data and experience with existing single-cell methods and software would represent a strong advantage. Excellent communication skills and team spirit, and an ability to work in
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 3 months ago
techniques will be explored to guide the inversion process. For instance, generative models (e.g., variational autoencoders or generative adversarial networks) can be employed to learn low-dimensional priors