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Sorbonne Université SIS (Sciences, Ingénierie, Santé) | Paris 15, le de France | France | 12 days ago
11 Mar 2026 Job Information Organisation/Company Sorbonne Université SIS (Sciences, Ingénierie, Santé) Research Field Technology Researcher Profile Recognised Researcher (R2) Leading Researcher (R4
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the conceptual foundations for modern AI, and where the world's first stored-programme computer ran in 1948. Data science and AI are now embedded as a core strategic priority for the university, making this a
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, Telecommunications, Artificial Intelligence or Computer Engineering; Mathematics; or a related field. Training or experience in data science, deep learning, and artificial intelligence. Knowledge of Python, PyTorch
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The Program in Computing for the Arts and Sciences (PCAS) is looking to hire one (1) GSI in the fall 2026 term to manage undergraduate instructional aides (IAs), grade, and lead lab sections for faculty
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and Advanced (shared), Anesthesiology and Surgery (shared), Soft Tissue Surgery (shared), Urological and Genital Diseases (shared), Neurological and Musculoskeletal Diseases (shared), Diagnostic Imaging
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): https://extranet.cing.ac.cy/images/media/redirectfile/PhD%20Topics%20BOOKLET%202026-2027.pdf . Where to apply Website https://extranet.cing.ac.cy/applynow Requirements Research FieldMedical sciences
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Engineering, Biomechanics, Computer Science, or related field Preferred Experience: Experience with machine learning in medical imaging/biomechanics; grant writing support; clinical gait analysis in clinical
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faculty with joint appointments in Music, Computer Sciences, Political Science and Communication Sciences and Disorders. In addition to internationally recognized efforts in psychological, cognitive and
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procedures; coordinate the administration of sedation to patients when necessary; under the direction of a physician; administer contrast media; maintain adequate computer and/or written records using
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applications. Key Responsibilities: Develop and fine-tune computer-vision models, instance segmentation, and retrieval-based estimation from images and text metadata. Build and evaluate monocular depth pipelines