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dimensional information, classification and/or deep learning methods may also be developed. In addition, the complementarity between the different data sources used (particularly between aerial LiDAR data and
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in the area of scientific computing and Computational Fluid Dynamics. Prior Experience in turbulence modelling, machine learning or the Lattice Boltzmann method is an advantage. Operational skills
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Skills/Qualifications Strong background in Operating Systems and Linux development Knowledge of memory management mechanisms and system-level programming Experience with Machine Learning models (design
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copolymers, which will then be evaluated for their degradability and mechanical properties. Using active learning, a branch of AI, the research will be guided through the large parameter space of copolymers
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at conferences and congresses Research will be carried out in either French or English, although non-French-speaking candidates are expected to make every effort to learn basic French to facilitate communication
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research and excellent digital literacy Strong interest in historical data, machine learning, data visualization, or digital hermeneutics Strong communication skills in English and good knowledge of French
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- Ability to learn on your own and develop skills The candidate must be able to work in a team on a multidisciplinary project. Applications should include a detailed CV; at least two references (people who
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(ROOT), • Physics: Experience in particle spectroscopy, heavy-ion reactions, fission dynamics Soft skills : • Teaching skills and the ability to instruct less senior scientists (Ph.D. and
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experimental parameters (time, temperature). To optimize these parameters, active learning techniques based on Bayesian optimization will be applied. In situ or ex situ characterizations (FTIR, ¹¹B/¹H NMR, HP
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in all areas · Personalized learning programme to foster our staff’s soft and technical skills · Multicultural and international work environment with more than 50 nationalities