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develop a new generation of hybrid models combining large-scale machine learning with physical knowledge to represent interactions between mobile robots and their environment. The research will address
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different dyadic motor coordination tasks. A range of neurophysiological measures (EEG, ECG and fNIRS) as well as behavioural measures will be recorded simultaneously from both partners. Machine-learning
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language processing that address concrete problems and are both theoretically rigorous and interpretable. The PhD is funded by the ERC CoG PANDORA (Deep Multimodal Learning for Mining and Generation of Arguments
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Eligibility criteria Selection will be based on the following scientific and technical criteria: • PhD in computational biology, machine learning, bioinformatics or a related field. • Proficiency with Python
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is to learn and repeat a path using both electric sensing and underwater vision, combining their strengths to improve robustness and flexibility. Approach This PhD project draws inspiration from
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to correlate polymerisation kinetics, macromolecular architecture, morphological evolution and drug encapsulation mechanisms. Beyond experimental work, the project will integrate machine learning approaches
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16 Jul 2026 Job Information Organisation/Company CNRS Department Architecture et Réactivité de l'ARN Research Field Chemistry Physics » Biophysics Biological sciences » Biological engineering
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the PhD project will be to acquire a thorough understanding of the PROVERIF resolution engine and its underlying theoretical foundations. The main scientific goal will then be to extend this resolution
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) and/or machine learning (about 10 PIs). The Physics Laboratory is about 180-member strong and conducts world-leading research on a broad range of topics, including quantum technology, statistical
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, machine learning, explainable artificial intelligence (XAI), digital twins, and integrated data-model approaches. • Study of the frugality of the developed approaches by reducing the requirements