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the Grenoble synchrotron. You will join the group responsible for developing diffraction analysis algorithms at the Grenoble synchrotron. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5510
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of Oxford. The post is funded by the National Institute for Health and Care Research (NIHR) and is fixed term for 24 months. The researcher will develop multi-sensor 3D reconstruction algorithms to fuse
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training algorithms and AI architecture. Image reconstruction, segmentation, and classification. High performance computing for spatiotemporal data. Major Duties/Responsibilities: Develop foundation AI
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computational frameworks that combine 4D point cloud data, geospatial analysis, and advanced ML/DL algorithms. Integrate dynamic environmental datasets into immersive and interactive prototypes for scenario
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deep learning algorithms. We welcome applications from individuals with experience in: Experience developing deep learning models for real-time image/video segmentation, object tracking, reinforcement
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algorithms that maximize the information extracted from images and delivered to the robot. To be successful in this role, we are looking for candidates to have the following skills and experience. We welcome
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. Qualifications Required Qualifications: Completed PhD in biomedical engineering, electrical engineering, physics, or a medical imaging related field. Experience with developing advanced pulse sequences
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of the extraction and beneficiation system. This work will require an understanding of mining processes, mathematical modeling of flows and extraction decisions, and the use of machine learning algorithms to predict
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of the algorithms developed in this project. About you The University values courage and creativity; openness and engagement; inclusion and diversity; and respect and integrity. As such, we see the importance
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an integrated development of network architectures, resource efficient algorithms, and programming paradigms for enabling an application-tailored design of dependable communication and computation systems