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Field
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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 2 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 2 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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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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for autonomous systems; field robotics; ● Cognitive Robotics: explainable artificial intelligence, perception-based interaction, and meta-reasoning to improve team performance; ●Human-Robot Interaction: Human
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computer science, statistics, computer engineering, artificial intelligence, machine learning, complex adaptive systems, agent-based modeling, agent-based computation economics, data science, computational
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. This fellowship focuses on examining the ethical, societal, and philosophical implications of artificial intelligence as it continues to evolve and integrate into various aspects of everyday life. The aim is to
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professional deliverables ● Experience with causal inference, machine learning, and artificial intelligence is desirable ● Experience with clinical, EHR, or biobank data analyses is desirable