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machine learning methods for signal processing, image analysis, data fusion, and prediction; build physics-informed and hybrid AI models that combine geophysical knowledge with data-driven approaches
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., Claude Code) Strong mathematical foundation relevant to quantitative image analysis (optimization, regression, statistics, signal processing, cluster analysis, machine learning) Advanced skills in
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. To be successful in this role you need to have the following qualifications A PhD in Computer Science, Applied Mathematics, Physics, Engineering, Scientific Computing, Image Processing, Data Science
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-ray tomographs of the BM05 beamline. Where to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR5521-LAUORG-010/Default.aspx Requirements Research Field Engineering Education Level PhD or equivalent
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Develop event-driven algorithms and software components for autonomous experiment control and adaptive image acquisition Build scalable, maintainable, and open-source software for high-throughput image
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institution. Advanced knowledge in proximal/remote sensing, cameras. Advanced knowledge in image processing and programming. At least 2 years of relevant experience, and willingness to work with agritech IoT
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spoken, as the department and project operate in a multilingual environment. Required qualifications: Master's degree in Engineering (M.Sc. Eng.) or equivalent. Experience in handling and processing
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science AI initiatives. What You’ll Do Develop software and AI-driven tools for image capture, volumetric data processing, and visualization Design and implement applications for photogrammetry, multi
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processing, computational statistics, and biomedical engineering. The post will involve liaising closely with the Oxford-based lab, including exchange visits to Oxford. This post represents a uniquely
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, signal and image processing, data-driven and physics-based models, as well as clinical validation and implementation. Neuroengineering increasingly incorporates AI‑based approaches to support