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Field
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year-long module performance in the water industry; (ii) exploring whether machine learning, couple with transport informed models can be used to predict membrane fouling for specific applications
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hemocompatible coating strategies to improve membrane–blood interactions. - Model and optimize membrane performance using computational tools, machine learning, and artificial intelligence Work Plan - Synthesis
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 5 days ago
learning and have strong mathematical skills. Knowledge of bandit models is a plus. LanguagesFRENCHLevelBasic LanguagesENGLISHLevelGood Additional Information Benefits Subsidized meals Partial reimbursement
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foundation-model experiments. Your role We are seeking a highly motivated Postdoctoral Researcher to join the FNR AI-HPC 2025 BRIDGES project GenePPS, which investigates how machine learning can enable
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new insights into the phenomena observed and enrich the databases required for deep learning methods. The neural networks currently being developed at LISTIC to detect and segment areas of movement in
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. Preferred Qualifications: Knowledge of computer models on watershed assessment and/or flood management. Knowledge of programming or scripting languages such as Python, Fortran, R, or others. Experience in
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discipline Strong experience in integrating several of the following components: Deep learning and LLMs for molecular biology Vision foundation models for pathological image analysis Multi-omics datasets (e.g
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analyses. Machine learning for biological data (e.g., protein language models, transformers, generative models) and interest in building interpretable tools for experimental colleagues. Qualifications PhD
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programming and data analysis (Python, MATLAB, or equivalent). Experience with machine learning, data-driven modeling, or AI methods applied to physical sciences datasets. Familiarity with handling and
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, machine-learning model development, structural sensing and health monitoring, conducting physical experiments, and validation of computational models. Required Qualifications: A successful applicant must