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agents and as photosensitizers. The PhD student will acquire expertise in techniques for studying ROS generation in solution (indirect methods using internal dyes) and in vitro (using ROS-active dyes
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parameters to identify regimes that ensure both flame stability and low pollutant emissions. Machine learning techniques have recently shown promise for Design of Experiments (DoE) and interpretation of large
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with both the CNRS and UGA, organized into five research teams conducting work in cognitive science (Body and Space, Development and Learning, Language, Consciousness, Memory & Metacognition, Vision
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algorithms for optimization Quantum annealing Quantum inspired optimization Quantum machine learning with a special emphasis on classical optimization of QML algorithms Noise mitigation in relation
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(with openness to learning others): Computational protein design or molecular modeling Protein biochemistry / structural biology Cell biology and receptor signaling Good communication skills in English
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sometimes struggle to effectively sustain patients' learning throughout their rehabilitation journey and may not adapt to the evolution of their abilities. Rehabilitation is a complex process that requires
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experimental data (from ex-situ and in-situ measurement). Therefore, she/he will develop a way to optimize/guide the experiments trough artificial intelligence approach (machine/deep learning) that he will
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, a protein expressed in many cancers, which is an indispensable element of the meiotic DSB formation machinery, but which exact function is not known. In order to learn more about MEI4 and its partners
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, engineering, bioinformatics, machine learning, artificial intelligence) to support minimally invasive and targeted preventive and predictive medicine capable of limiting age-related functional disorders
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by exploiting foundational machine-learning potentials such as MACE, SevenNet, or Orb-V3. The predictions will then be progressively refined and verified by DFT and, ultimately, tested experimentally