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Position Data Science and Artificial Intelligence in Cardiac Electrophysiology Our goal: the development of multimodal prediction models to detect and predict atrial fibrillation (AF) and other clinically
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to apply Website https://brgm-recrute.talent-soft.com/job/emploi-these-en-intelligence-artificie… Requirements Research FieldGeosciences » GeologyEducation LevelMaster Degree or equivalent Additional
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required. Candidates with experience in artificial intelligence techniques in radiation therapy, imaging analysis, bio-physics modeling and big data management would be preferable. It is also desirable
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engagement, and experiential learning. · Teach undergraduate and/or graduate courses in cybersecurity, computer engineering, artificial intelligence, and related areas. · Develop and update course materials to
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/JPL (https://costar.jpl.nasa.gov/ ). Subject description Robotics and artificial intelligence aim to develop novel robotic systems that are characterized by advanced autonomy for improving the ability
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/JPL (https://costar.jpl.nasa.gov/ ). Subject description Robotics and artificial intelligence aim to develop novel robotic systems that are characterized by advanced autonomy for improving the ability
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on explainable artificial intelligence and intrusion detection for healthcare cybersecurity. The position will contribute to the design, implementation, evaluation, and documentation of machine learning and
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to tackling the challenges that China and the world are facing in the fields covering artificial intelligence, biology, biomedical engineering, data science, electrical engineering, energy, environment, human
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, combining plasma proteomics with artificial intelligence may enable the minimally invasive assessment of organ-specific biological age and functional decline. This project aims to develop organ-age and organ
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Institute, the Thomas Ashton Institute, the Tyndall Centre for Climate Change Research, the Dalton Nuclear Institute, the Institute for Data Science and Artificial Intelligence, and the Christabel Pankhurst