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Field
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-motivated person to lead OME initiatives designed to advance knowledge of the role of advanced data systems (e.g. Artificial Intelligence (AI), Virtual Reality (VR)) in public health applications and
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wildfire simulation, fuel modeling, remote sensing, data-driven methods, artificial intelligence, and real-time applications. The successful candidates will contribute to the development of faster than real
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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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develop and apply computational approaches for mass spectrometry data, with artificial intelligence/machine learning (AI/ML) being a major focus. They will have an opportunity to lead and contribute to a
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 4 hours ago
Experience Requirements Applicants should have (or expect to receive before the start of the position) a PhD in Computer Science or EE/ECE on a topic in machine learning, artificial intelligence, natural
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 4 hours ago
the ability to design and implement novel artificial intelligence algorithms. Examples of research directions could include: multimodal foundational models for biomedical data, deep-learning architectures
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holding a PhD in chemical, environmental or process engineering, to apply for a full-time post-doctoral fellowship position in the field of water desalination, focusing on the development of an artificial
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will use our Campus Values to guide their decisions and actions and demonstrate our Rebel spirit. PREFERRED QUALIFICATIONS Experience applying machine learning (ML) or artificial intelligence (AI
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to the cultivation and analysis of colon bacteria in order to study their physiology, function and interactions. We are also a member of VIB.AI, the newly founded center for artificial intelligence applications in
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navigation simulations for early mission studies; integration with study teams for onboard autonomy simulations (e.g. intelligent failure and contingency handlers); application to close proximity operations