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Field
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This position focuses on advancing the mathematical and computational foundations of interpretable algorithms for dynamical systems and explainable AI. The successful candidate will develop new
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developing representations, using neuroimaging with fMRI and OPM-MEG, and to model the developmental process using computational models from AI. The project aims to better understand infant cognition, develop
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at the intersection of algorithmic guidance and management. These issues have become more pressing as generative AI offers potential productivity gains while also making it easier to conceal effort. A first study
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members Sriram Pemmaraju and Sourya Roy on sampling problems in the distributed and parallel computing setting. The ideal candidate will have research experience in sampling algorithms and related areas
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safety and computational social choice and develops formal frameworks and algorithms for eliciting, aggregating, and analysing stakeholder preferences over risk and safety in AI systems. The Research
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research, computer science, or a related field. The appointment is typically for one year and may be extended, subjected to performance and availability of research funding. Key Responsibilities: Conduct
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Dunedin and will be supervised by Associate Professor Colin Fox. The successful applicant will play a leading role in developing scalable Bayesian algorithms, probabilistic models, and computational methods
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11 Jul 2026 Job Information Organisation/Company CNRS Department Laboratoire d'Informatique de l'Ecole Polytechnique Research Field Computer science Mathematics » Algorithms Researcher Profile First
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trajectory optimization, nonlinear programming, or genetic algorithms. High-performance computing (HPC), parallel numerical workflows, or GPU-accelerated model execution. Terms of Appointment This is a full
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the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Technological developments and the availability