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surfaces. Consequently, it is essential to develop mobile measurement instruments and acquire comprehensive datasets to validate and enhance the models. This PhD thesis project, a collaboration between COLAS
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existing SC analysis tool, by integrating machine learning and benchmarking components, thus helping evolve it into a market-ready solution capable of real-time threat intelligence and adaptive vulnerability
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neural network or other machine learning method are available and should be evaluated before implementation. The simulator can then be used to study the nocivity of natural and synthetic ground motion
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from our competitive compensation and allowancespackage, including financial support for your relocation to Grenoble Where to apply Website https://jobstats.robopost.com/count/clic.php?v=2235560&j=636
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with machine learning approaches Knowledge of muscle mechanics (Hill muscle model or similar) Previous work on simulated bodies or animal locomotion Your Role You will work collaboratively with a
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Arts et Métiers Institute of Technology (ENSAM) | Paris 15, le de France | France | about 2 months ago
can be developed using FPBTs and FBGs coupled with physically informed (PI) machine learning algorithms. SMATSH scientific objectives are then to develop computationally efficient models to predict
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materials science, - Machine learning force fields / data-driven techniques for chemistry or materials science Specific Requirements This position involves a significant amount of numerical code development
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-driven drug development. Mentor junior team members and provide domain expertise to our R&D team. Bridge Research & Product: Translate biopharma research questions into actionable machine learning
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, T., ... & Thouvenin, O. (2023). Automatic diagnosis and classification of breast surgical samples with dynamic full-field OCT and machine learning. Journal of Medical Imaging, 10(3), 034504-034504. [3