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algorithms for the next generation of particle physics experiments and also explores other ways AI can accelerate scientific discovery. The group collaborates closely with computer scientists, astrophysicists
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by combining psychological profiling, biological lab data, physiological time series, and sensor data. The postdoc will play a leading role in developing and implementing predictive algorithms designed
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to be developed: Analyze iEEG data. Develop multimodal algorithms. Perform the characterization of the epileptogenic network. Where to apply Website https://seuelectronica.upc.edu/en/procedures/call-for
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foundations, focusing on the structure and complexity of quantum computational models; (ii) optimization and related graph-theoretic methods, using polyhedral geometry and algorithmic optimization (e.g., vertex
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learning models to accelerate mixed-integer solvers Implementing and analysing online optimisation algorithms for real-time grid balancing Liaising with project partners (NESO and University of Strathclyde
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networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis
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for excellent and highly motivated researchers in all areas of the field, including but not limited to: quantum algorithms and complexity; quantum information theory; quantum cryptography; quantum information in
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algorithms Designing new algorithms and investigating their mathematical performance guarantees Participate in writing up the results and submission for scientific publication Collaborate with and mentor
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25 Jan 2026 Job Information Organisation/Company CNRS Department Institut de Recherche en Informatique Fondamentale Research Field Computer science Mathematics » Algorithms Researcher Profile First
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solvers • Implementing and analysing online optimisation algorithms for real-time grid balancing • Liaising with project partners (NESO and University of Strathclyde) Essential selection