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Charles Henry Turner Post-doctoral Fellow, Department of Geography & GIS, College of Arts & Sciences
. Job Overview The Department of Geography and GIS at the University of Cincinnati, Ohio, seeks a fellow in geography, geospatial artificial intelligence (GeoAI), and spatial data science for its Charles
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Artificial Intelligence (AI)-enabled restructuring. The Postdoctoral Associate will work with ILR faculty member Virginia Doellgast in the Department of Global Labor and Work. In addition to working
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Postdoctoral Research Associate will contribute to developing and/or applying artificial intelligence, machine learning, and image segmentation and/or data science-based methods to address cutting-edge topics
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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
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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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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day 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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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day 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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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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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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in the Department of Urology at the Stanford University School of Medicine and will be affiliated with Department of Radiation Oncology and the Center for Artificial Intelligence in Medicine & Imaging