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data analytics, and manufacturing process optimization. Develop and apply models, algorithms, or data analysis workflows to support machining process understanding, machine tool characterization, process
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the project. What you will do Conduct original and high-quality research in machine learning and computer vision; Develop novel algorithms for adapting and specialising visual foundation models; Publish
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. Development of real-time optimization algorithms and model predictive control (MPC) strategies for adaptive process management. Addressing data sparsity and data quality issues in industrial process data
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associate will work both independently and collaboratively to develop and apply novel deep learning algorithms and/or computational chemistry methods for small-molecule drug discovery targeting RNA
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digital worlds. Its teams explore, design, and develop models and methodsboth physical and algorithmic—as well as new technologies that bridge the real world (matter and living systems), digital data, and
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; Develop novel algorithms for adapting and specialising visual foundation models; Publish research findings at leading machine learning and computer vision venues such as CVPR, ICCV, ECCV, NeurIPS, and ICLR
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observations. The UH team has developed an approach, where simulation data is projected into observation-space quantities while the workflow is active, enabling both run-time reality check and rigorous posterior
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23 Jun 2026 Job Information Organisation/Company CNRS Department Heuristique et Diagnostic des Systèmes Complexes Research Field Computer science Mathematics » Algorithms Researcher Profile First
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, the present research task focuses on evaluation of Climate DT simulation quality via direct use of raw Earth observations. The UH team has developed an approach, where simulation data is projected
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: develop physics-informed and physics-grounded world models that remain reliable under partial observation, where pure physics engines fall short; design methods that achieve large speed-ups in complex