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remaining biologically interpretable? The PhD candidate will design and apply integrative computational workflows using methods such as multi-omics integration, spatial modelling, representation learning
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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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production. By developing hybrid architectures combining ontologies, generative models, reinforcement learning, and uncertainty quantification, the PhD project addresses the challenges identified by ICCARE in
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of technological disruption driven by Artificial Intelligence, we propose to analyze the data and quantify these similarities by exploring various applications of machine learning methods. With the advancement of AI
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archaeological and historical contexts is also required. Additionally, the ability to perform *ad hoc* data processing (multivariate statistics, machine learning, etc.) is desirable. Proficiency in programming
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are seeking a candidate holding a Master 2 degree in computational biophysics, structural bioinformatics, or a related field. Knowledge of statistical mechanics and/or machine learning would be an asset
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and validated within the PhLAM team. Consequently, only limited effort will be required to acquire the experimental skills needed for this part of the project, allowing the PhD candidate to focus
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modern machine-learning techniques, will be exploited to improve the discrimination between the different polarization states. The analysis will use the complete Run 2 and Run 3 datasets collected by
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, or roundabout navigation will be considered. In this work, we also aim to explore the use of machine learning approaches [1][2] to personalize the driving system according to individual driver preferences
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member of the French metrology network FIRST-TF, and a member of the REFIMEVE+ project, which physically links our institute to the LTE laboratory in Paris. This thesis will allow the candidate to acquire