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of this project for a one-year period (100% full-time commitment) to make a significant contribution to the implementation of machine learning (ML) algorithms. The postdoc is expected to have proven experience in
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” and “wet” lab workflows). You will be able to Design, develop and implement algorithms and systems based on foundation models, large language models and/or AI agents for automated scientific discovery
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experts. You will design imaging sequences and develop beamforming and signal processing algorithms to achieve ultrafast frame rates and detailed visualization of cerebral vasculature. You will work closely
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more than 300 employees with competencies in electrical and photonics engineering. Research is performed within nanophotonics, lasers, quantum photonics, optical sensors, LEDs, photovoltaics, ultra-high speed
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Regularization. We aim to develop mathematical understanding of implicit regularisation properties in deep neural networks to guide the development of algorithmic paradigms aimed at combining statistical
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participation in the DARPA SubT challenge (https://robotics.fel.cvut.cz/cras/darpa-subt/ ) and several state-of-the-art robotics platforms and sensors (https://robotics.fel.cvut.cz/cras/robots/ ). The Department
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limited to: Implement, optimize, and evaluate efficient algorithms and software tools applied to reference genome assembly and curation, and to the analysis of genomic data broadly Contribute
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 3 months ago
algorithms able to provide decision making in uncertain environments. He was PI of several projects, including ANR-JCJC project BADASS (BAnDits Against non-Stationarity and Structure), Inria Action
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lattice models. We welcome applications of candidates from a wide range of backgrounds from theoretical physics to pure mathematics. Candidates with experience in tensor network algorithms, rigorous
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sensor geometric sensor data with simulation for real-time control and adaptive assembly. This builds on existing work within the group on digital twins for geometry assurance. AI for automatic tolerance