The University of Nevada, Las Vegas invites applications for an Assistant Professor of Big Data Science in Public Health in the Department of Healthcare Administration & Policy in the School of Public Health. This is a full-time, tenure-track position which is part of an interdisciplinary cluster hire. We seek applicants with a multidisciplinary background and strong research experience utilizing a combination of technologies/techniques, including any area with a strong focus on data, broadly construed. ROLE of the POSITION The ideal candidate will contribute to and expand existing big data and informatics research within the School of Public Health (SPH), advancing innovative, multidisciplinary approaches to healthcare and public health challenges. Candidates should possess a strong, interdisciplinary background and a demonstrated record of research that integrates multiple technologies and analytical methodologies. Candidates with a strong foundation in information technology, data analytics, and emerging digital health technologies and their application in healthcare and public health settings are especially encouraged to apply. Experience in applying big data frameworks to AI-driven solutions, including deep learning and natural language processing, is considered a significant asset. This position is a part of campus-wide cluster hiring opportunity in areas of strategic importance to Southern Nevada. The person hired for this position will be expected to collaborate with faculty in multiple departments and research areas in the SPH and will support interdisciplinary research in the above topics; further, there will be opportunities to work collaboratively with units across the university campus in support of health-related big data research. Experience working with public health data and/or within healthcare analytics organizations is a plus. Requirements also include publishing research, seeking extramural funding, service to professional associations, and serving on department, college, and university committees.
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Job Type
Full-time
Career Level
Mid Level
Education Level
Ph.D. or professional degree
Number of Employees
1,001-5,000 employees