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This multidisciplinary thesis requires strong expertise in several of the following areas: Robotics, computer vision, control systems, dynamic modeling, signal processing, or machine 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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. Depending on the candidate's profile and interests, the thesis may develop along one or several of the following directions, at the crossroads of statistical physics, biophysics, and machine learning
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Eligibility criteria The recruited person must have expertise in cosmology, numerical development and machine learning. They must be proficient in the Python programming language, with experience in JAX being a
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of Research Experience1 - 4 Additional Information Eligibility criteria We are looking for a doctor in particle physics with less than two years of experience after the PhD. Experience in machine learning and
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data) will help validate observations and refine predictive models. Automated monitoring tools (scripts, dashboards, alerts) incorporating machine learning algorithms or statistical methods will be
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/F) will work within the “RNA Architecture and Reactivity” unit and join the “Structure, Dynamics, and Targeting of Biomolecular Machines” team. This team currently consists of 6 researchers, 3
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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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, ideally molecular dynamics and/or DFT. Scientific programming skills, particularly in Python, are expected. Familiarity with machine learning or generative AI methods applied to materials would be a strong
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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