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combines: Fluid dynamics and heat transfer (theory and experiments), Computational modeling, and Machine learning / computer vision for data analysis and pattern recognition. The goal is to improve
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innovations, OCTO Technology and the PIMM laboratory at ENSAM are jointly sponsoring this PhD thesis. The research will focus on the application of Physics-Informed Machine Learning (PIML) and Physics-Informed
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PhD candidate will have: Master’s degree (or equivalent) in Human-Computer Interaction, Psychology, or Disability Studies Strong interest in accessibility, assistive technology, human-computer
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machine learning with the logical reasoning and semantic understanding of symbolic AI (often referred to as material and design informatics) is being developed for the accelerated discovery and development
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consider novel design principles combining approaches in biosensors, communication systems, and machine learning. Are you motivated to take a step towards a doctorate and open up exciting career
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Academically relevant background within marine control/cybernetics, computer science, or hydrodynamics, with good skills in mathematics, programming, and machine learning. Master's degree in control engineering
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? No Offer Description Job description Consortium This position is part of a European Doctoral Network consortium "Machine learning for integrated multi-parametric enzyme and bioprocess design", where 15
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biology, or analytical workflows. Interest in single-cell analysis, cancer biology, and translational research. Basic level expertise in computational biology (e.g., bioinformatics, machine learning), with
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and Gabriele Keller) and machine learning (e.g., Bob Carpenter) if appropriate for your interests. Beyond membership of the FoRECAST team, you’ll join the Software Technology group led by Gabriele
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by detecting and predicting threats such as pests, diseases, and environmental stress in line with the UK Plant Biosecurity Strategy. The project harnesses computer vision, deep learning, and large