UNIV - Research Assistant Professor - Department of PHS
About The Position
The Division of Biomedical Informatics and AI in the Department of Public Health Sciences at the Medical University of South Carolina (MUSC) is seeking a research-track Assistant Professor to conduct methodological research in biomedical informatics, artificial intelligence, and biomedical applications. The successful candidate will maintain an extramurally funded research program and teach in the Department of Public Health Sciences graduate programs. The position also offers expertise to related research cores, including machine-learning analysis of health data and AI-assisted medical evidence synthesis. The division is a growing unit focused on advancing data-driven health research and education. MUSC is an academic medical center in Charleston, South Carolina, with programs in biomedical research, informatics, and health innovation.
Requirements
- PhD in Biomedical Informatics, Computer Science, Biostatistics, Bioinformatics, or another relevant area, or an MD with appropriate technical education and experience.
- Proven teaching experience at the graduate or doctoral level.
- Research experience in biomedical informatics and AI technologies in one or more relevant areas, including data science, machine learning, artificial intelligence, or multivariate analysis applied to biomedical data; quantitative or AI research using electronic health records; applications of large language models to biomedical research, literature curation, or knowledge extraction; or other biomedical informatics research areas.
- Strong communication skills.
Nice To Haves
- Postdoctoral fellowship training in biomedical informatics.
- A strong research record, including publications and extramural funding.
- Participation in leading medical informatics conferences, such as AMIA, and related working groups.
Responsibilities
- Maintain an extramurally funded research program.
- Teach in the Department of Public Health Sciences graduate programs.
- Offer expertise to related research cores, such as machine-learning analysis of health data and AI-assisted medical evidence synthesis.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree
