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Multi-modal Machine Learning—including areas like Neuro-symbolic AI, Knowledge Graphs, Contextual AI, Conversational AI, and Trustworthy & Safe AI. This role also offers the opportunity to explore human
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Candidates MD, DO, MBBS, PhD, EdD, or equivalent in a related field such as the health sciences, education or other field given context of work experience and/or other qualifications. Qualified for a faculty
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: Doctorat de l'Université Grenoble Alpes PHD Country: France Where to apply Website https://www.abg.asso.fr/fr/candidatOffres/show/id_offre/136951 Requirements Specific Requirements With a Master degree, or
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2026. Area of specialization within the field of Sustainability is open, but the candidate must be able to teach a range of lower and upper-level courses in service to innovative interdisciplinary B.A
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contributions in one or more of the following key areas: computational modeling of chemical systems, AI-driven materials discovery/design, robotics for chemical synthesis, machine learning applications in
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University Department of Physics invites applications for a full-time non-tenure track appointment at the rank of Instructor to primarily teach introductory physics in the fall 2026 and spring 2027 semesters
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of this PhD is to develop physics-informed neural operator frameworks that embed governing equations and invariants of fluid mechanics directly into learning architectures, enabling real-time, generalizable
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to an advanced Laboratory Directed Research and Development (LDRD) project, "Machine Learning Steered EXAFS Fitting for Autonomous XAS Analysis," aimed at revolutionizing real-time analysis of X-ray Absorption
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with experience in ligand discovery. Our research group is focused on developing state-of-the-art computational methods for ligand/drug discovery, using machine learning, high-performance/cloud computing
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Posting Summary Logo Posting Number RTF00050PO26 USC Market Title Associate Scientist Link to USC Market Title https://uscjobs.sc.edu/titles/156374 Business Title (Internal Title) Associate