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in quantitative methods. Must have high proficiency in R and/or other computer programming languages. Applicants in All But Degree Status will be considered for interviews. Preferred Qualifications
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research in the natural, mathematical and computer sciences with a focus on the processing, structuring, and analyzing of large amounts of complex data and the development of computational methods and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
department in 1964. We believe that computer science’s greatest purpose is in working with other scientists to solve problems in their own disciplines. Therefore, we actively seek opportunities to generate new
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meetings, progress reports, conferences, seminars, symposia, and assist in drafting relevant publications and grant proposals. The candidate must be proficient in standard computer skills relevant to the job
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with others and contribute to a team environment. Technical Proficiency: Skilled in using office software, technology, and relevant computer applications. Communication: Strong and clear written and
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environments, approaches related questions in an interdisciplinary manner (i.e., at the intersection of psychology, technology, and human–computer interaction). We welcome candidates with a strong interest in
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communication skills. Must be computer literate with proficiency and working knowledge of database and reporting tools such as Microsoft Word, Excel, Access, and PowerPoint. Preferred Qualifications Equipment
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SAS and/or R programming skills. Effective oral communication skills. Must be computer literate with proficiency and working knowledge of database and reporting tools such as Microsoft Word, Excel
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Interaction (HCI), with emphasis on user experience design, prototyping, accessibility, and usability evaluation. The Research Fellow will investigate how interactive technologies can be designed to respond
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expertise in specialised domains where labelled data is scarce. Recent foundation models have transformed computer vision, yet their ability to acquire new expertise remains limited when training data is