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nonlinearities, reinforcement learning for predictive control, and digital twins to bridge simulation and real-world deployment. The next step is on-sky demonstration, supported by access to telecom and astronomy
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here is the prediction of the composition of communities of marine entities (zooplankton, marine snow particles, and coral reef fishes) from environmental data taken around the point of the biological
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of the variability and uncertainty of simulated outputs • an explicit quantification of prediction error • an interpretable and controllable structure (e.g., Gaussian processes, …) 2. Model industrial system
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of the interface, the mobility of lithium and electronic charges at this level, using materials with controlled morphology and surface state, through isotopic exchange techniques and/or homo/heteronuclear
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Université Grenoble Alpes, laboratoire TIMC, équipe GMCAO | Grenoble, Rhone Alpes | France | 13 days ago
multi-expert segmentation databases. The postdoctoral fellow will focus on integrating segmentation variability into deep learning models, with the goal of assessing prediction reliability and enabling
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Infrastructure? No Offer Description The postdoctoral researcher will contribute to the ANR-funded Pi-CANTHERM project, which aims to design, model, and predict the performance of new n‑type organic thermoelectric
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and localization of a potential fault using the Matched Field Processing (MFP) method, based on the reconstruction of a response model of the inspected structure from the modal parameters predicted by
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Postdoctoral position: Developing a human lymphoid organ-on-chip to evaluate candidate mRNA vaccines
Chakrabarti at the Pasteur Institute in Paris. The position is fully funded for 3 years in the frame of an industrial contract. Predicting the immunogenicity of candidate vaccines in humans remains a challenge
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coordinated mechanisms, which include DNA Damage Response (DDR), the control of cellular proliferation or apoptosis induction. IR exposure might lead to genomic instability, chromosomal aberrations and cancer
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health and translational medicine using a "bench-to-bedside" approach. By harmonising and analysing diverse biomedical data, while focusing on the secure data processing and predictive modelling, we aim