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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 20 hours ago
of drug development, regulatory science, and advanced computational modeling. This position will involve integrating mechanistic modeling and machine learning methods to analyze and predict drug properties
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an advanced AI-augmented digital platform (AiCT-Med) powered by cutting edge machine learning models trained on multiple large, aged care datasets from providers across Australia. The platform is designed
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UCD Center for Labor and Community - Engaged Research Fellowship Project Coordinator (PROJECT POLICY
marketing materials based on intended audience (colleagues, faculty, students, employers, etc.). Advanced computer skills in Microsoft and Mac environment, including, Access, Word, Excel, PowerPoint and
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UCD Center for Labor and Community - Engaged Research Fellowship Project Coordinator (PROJECT POLICY
requirements, and changing priorities. Skills to prepare data presentation and marketing materials based on intended audience (colleagues, faculty, students, employers, etc.). Advanced computer skills in
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Computer Science, Biomedical Engineering, Pathology Informatics, or a related field, with emphasis on computer vision and machine learning (summer and fall graduates are also welcome to apply) Proficiency in
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postgraduate-level research in Computer Science, Cybersecurity, Information Security, Information Technology, Artificial Intelligence, Machine Learning, or a related field, have experience with securing AI
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account options for medical and childcare expenses Robust free training access through LinkedIn Learning plus professional conference opportunities Tuition assistance Expansive employee discount program
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in conducting human behavioural experiments or human-centered field studies. Demonstrated experience in using machine learning, such as deep learning for image processing, or natural
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PhD in Aerospace Engineering, Mechanical Engineering, Electrical Engineering or Computer Science with a focus on dynamics and control. Additional Qualifications Considered PhD in Aerospace Engineering
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the following training will be considered PhD in computer science, machine learning, AI or related computational field, or, Ph.D. in a health-related discipline with experience in experimental science, devices