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data applications and the theoretical analysis of machine learning methods. A list of members of the statistics group can be found here . The Statistics group is embedded within a larger data science
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supervision signals (e.g., labels in a downstream task or symbolic constraints). You will perform machine learning research, developing a framework for learning interpretable and robust concepts with
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, multi-modal data, and GPU-accelerated machine learning for materials science. Information We are seeking two highly motivated postdoctoral researchers to join the Horizon Europe project SIMU-LINGUA, a
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modelling (e.g., agent-based Bayesian models, cognitive learning models, machine learning). Experience in annotation software such as ELAN and PRAAT. Existing peer-reviewed journal publications and conference
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to imagine novel task configurations and learn robust manipulation policies from just a few real demonstrations. You will work at the intersection of 3D computer vision, physical simulation, and robot learning
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for the efficient training and fine-tuning of machine learning models. The postdoc will closely collaborate with researchers at the Dutch Language Institute (and Radboud University Nijmegen). Selection Criteria PhD
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to offer a coherent, system-level perspective to guide its strategic evolution notably in the context of machine learning/artificial intelligence numerical, weather, ocean and climate prediction systems. By
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Vacancies Scientific programmer of libraries on testing and learning in Haskell and Python Key takeaways As a scientific programmer, you will support the development of software from a technical
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close collaboration with other discipline experts, such as software, microelectronics and applications engineers. * except for RF payloads. ** including artificial intelligence and machine learning
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advanced techniques (such as digital beamforming or machine learning/Al techniques) supporting instrument operation and operative modes; onboard data compression; onboard data encryption; ASICs and devices