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parameter-efficient fine-tuning, compare complementary foundation models and evaluate their representations through retrieval, clustering, classification and external validation. The resulting models will be
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29 Aug 2026 Job Information Organisation/Company ARCNL Research Field Engineering » Computer engineering Engineering » Precision engineering Physics » Computational physics Physics » Metrology
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Inria, the French national research institute for the digital sciences | Talence, Aquitaine | France | 2 months ago
simulation to reduce the real-to-sim gap; (ii) estimating each mechanism's performance and its sensitivity to variation in design or manufacturing parameters, such as used material, prototyping technology, or
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for analysing authentic, synthetic, and manipulated images or videos. The work will combine predictive performance with explainability, uncertainty estimation, robustness, and generalization. Attention will be
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models, parameter estimation and model validation). Documented knowledge and experience in data analysis and scientific computing (such as proficiency in Python/R/MATLAB, data visualization, machine
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approaches that reduce the dimensionality of parameter spaces and produce mechanistically realistic, experimentally testable predictions. As a result, systems-oriented biological research is inherently