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University of North Carolina Wilmington | Wilmington, North Carolina | United States | about 9 hours ago
, and artificial intelligence, and we conduct experiments with both healthy volunteers and clinical patients (PTSD, substance use disorders, mTBI). UNCW postdoctoral scholars gain important training and
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leverages the latest advancements in artificial intelligence/ machine learning (AI/ML) and high-performance computing to accelerate the discovery, design and synthesis of advanced functional materials
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addition to conventional tools such as XRD, BET, XRF, SEM, TEM, etc. Collaborate with computational modeling and artificial intelligence/machine learning teams to improve battery performance, using rational design
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curious to deliver work that matters, your journey starts here! The Machine Learning Department (MLD) is a leading hub for research and education in artificial intelligence and machine learning. It focuses
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: Artificial Intelligence / Machine Learning Knowledge Representation and NLP methods Clinical Informatics Bioinformatics Biomedical Ontology Public Health Informatics Nursing Informatics Imaging Informatics
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curious to deliver work that matters, your journey starts here! The Machine Learning Department (MLD) is a leading hub for research and education in artificial intelligence and machine learning. It focuses
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is intended to provide mentored research training and experience for a post doc fellow whose interests are aligned with the field of Technology Governance, which could include: artificial intelligence
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multidisciplinary team comprised of fellow postdoctoral appointees, experimentalists, and staff scientists, with computational fluid dynamics (CFD) and artificial intelligence/machine learning (AI/ML) expertise, with
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focus will be on exploring the utility of artificial intelligence models in the study of the above, studying quantum mechanical generalizations, and uncovering connections to statistical models. Position
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patients and established pipelines for data pre-processing, analysis, and integration (Good et al. Nat Med 2022; In Preparation). We now seek to build generative artificial intelligence (AI) models