About the role
The Division of Biomedical Informatics and AI in the Department of Public Health Sciences at the Medical University of South Carolina (MUSC) College of Medicine invites applications for a full-time, tenure-track or non-tenure track Assistant Professor position in Translational Bioinformatics.
Summary The Division of Biomedical Informatics and AI in the Department of Public Health Sciences at the Medical University of South Carolina (MUSC) College of Medicine invites applications for a full-time, tenure-track or non-tenure track Assistant Professor position in Translational Bioinformatics. We seek innovative and collaborative scientists whose research leverages large-scale human genomic and health data resources to advance precision medicine and improve human health.
Areas of interest include, but are not limited to, the analysis of electronic health record (EHR)-linked biobanks, human genetics and genomics, statistical genetics, genetic epidemiology, genome-wide and phenome-wide association studies (GWAS/PheWAS), pharmacogenomics, genomic medicine, and the development and application of artificial intelligence (AI) and machine learning (ML) methods for genomic and clinical data.
Successful candidates will establish impactful research programs focused on translating genomic discoveries into biological, clinical, and population health insights. Candidates with experience integrating multimodal data sources, including genomic, transcriptomic, sequencing, clinical, imaging, and other real-world data, are especially encouraged to apply. Faculty track will be commensurate with qualifications and experience.
Entity Medical University of South Carolina (MUSC - Univ) Worker Type Employee Worker Sub-Type Faculty Cost Center CC001035 COM PHS Administration CC Pay Rate Type Salary Pay Grade University-00
0.00 - 0.00 - 0.000 Scheduled Weekly Hours 40 Work Shift
The Division of Biomedical Informatics and AI in the Department of Public Health Sciences at the Medical University of South Carolina (MUSC) College of Medicine invites applications for a full-time, tenure-track or non-tenure track Assistant Professor position in Translational Bioinformatics. We seek innovative and collaborative scientists whose research leverages large-scale human genomic and health data resources to advance precision medicine and improve human health.
Areas of interest include, but are not limited to, the analysis of electronic health record (EHR)-linked biobanks, human genetics and genomics, statistical genetics, genetic epidemiology, genome-wide and phenome-wide association studies (GWAS/PheWAS), pharmacogenomics, genomic medicine, and the development and application of artificial intelligence (AI) and machine learning (ML) methods for genomic and clinical data.
Successful candidates will establish impactful research programs focused on translating genomic discoveries into biological, clinical, and population health insights. Candidates with experience integrating multimodal data sources, including genomic, transcriptomic, sequencing, clinical, imaging, and other real-world data, are especially encouraged to apply. Faculty track will be commensurate with qualifications and experience.
Key Responsibilities Develop and maintain an independent, nationally recognized, externally funded research program in translational bioinformatics, human genetics, genomics, precision medicine, and/or AI-enabled biomedical discovery. Conduct innovative research leveraging EHR-linked biobanks and large-scale genomic and clinical datasets to investigate disease risk, therapeutic response, and health outcomes. Develop and apply advanced statistical, computational, and AI/ML methods for the analysis of genomic, sequencing, phenotypic, and health-related data.
Lead and collaborate on studies involving GWAS, PheWAS, fine-mapping, polygenic risk modeling, pharmacogenomics, genetic epidemiology, genomic medicine, and related areas. Collaborate with investigators across MUSC, including clinical, translational, biomedical, public health, and data science researchers, to advance interdisciplinary research initiatives. Contribute to institutional efforts supporting precision medicine, biobank science, genomics, and AI-driven healthcare innovation.
Teach and mentor students, fellows, and trainees in biomedical informatics, data science, genetics, genomics, and related graduate education programs. Participate in the training and mentoring of the next generation of researchers through interdisciplinary research, educational, and workforce development initiatives. Contribute to service activities within the Division, Department, College, University, and the broader scientific community.
Qualifications PhD, MD, MD/PhD, or equivalent degree in biomedical informatics, computational biology, genetics/genomics, biostatistics, computer science, genetic epidemiology, or a related field. Demonstrated expertise in large-scale human genetic and genomic analyses, including GWAS, PheWAS, sequencing studies, and/or pharmacogenomics. Experience working with EHR-linked biobanks and real-world clinical data.
Evidence of developing or applying AI/ML methods to genomic, sequencing, multimodal, or healthcare data. Demonstrated research productivity and potential for securing independent funding. Commitment to excellence in teaching, mentoring, and interdisciplinary collaboration.
Start-Up and Support Successful candidates will receive a competitive start-up package, including dedicated research space, access to core facilities, and administrative support for grant development. MUSC is committed to fostering faculty development through mentorship, interdisciplinary collaboration, and integration with clinical and translational research initiatives. About the Division of Biomedical Informatics and AI Located within the Department of Public Health Sciences, the Division of Biomedical Informatics and AI is a dynamic and growing unit at MUSC focused on advancing data-driven health research and education.
MUSC is a premier academic medical center located in Charleston, SC, with nationally recognized programs in biomedical research, informatics, and health innovation. Additional
Physical
- (Note: The following descriptions are applicable to this section: Continuous - 6
- 8 hours per shift; Frequent - 2
- 6 hours per shift; Infrequent - 0
- 2 hours per shift) Ability to perform job functions in an upright position. (Frequent) Ability to perform job functions in a seated position. (Frequent) Ability to perform job functions while walking/mobile. (Frequent) Ability to work indoors. (Continuous) Ability to work outdoors in all weather and temperature extremes. (Infrequent) Ability to work in confined/cramped spaces. (Infrequent) Ability to perform job functions from kneeling positions. (Infrequent) Ability to squat and perform job functions. (Infrequent) Ability to perform 'pinching' operations. (Infrequent) Ability to fully use both hands/arms. (Frequent) Ability to perform repetitive motions with hands/wrists/elbows and shoulders. (Frequent) Ability to reach in all directions. (Frequent) Possess good finger dexterity. (Continuous) Ability to maintain tactile sensory functions. (Continuous) Ability to lift and carry 15 lbs., unassisted. (Infrequent) Ability to lift objects, up to 15 lbs., from floor level to height of 36 inches, unassisted. (Infrequent) Ability to lower objects, up to 15 lbs., from height of 36 inches to floor level, unassisted. (Infrequent) Ability to push/pull objects, up to 15 lbs., unassisted. (Infrequent) Ability to maintain 20/40 vision, corrected, in one eye or with both eyes. (Continuous) Ability to see and recognize objects close at hand. (Frequent) Ability to see and recognize objects at a distance. (Frequent) Ability to determine distance/relationship between objects; depth perception. (Continuous) Good peripheral vision capabilities. (Continuous) Ability to maintain hearing acuity, with correction. (Continuous) Ability to perform gross motor functions with frequent fine motor movements. (Frequent) If you like working with energetic enthusiastic individuals, you will enjoy your career with us! The Medical University of South Carolina is an Equal Opportunity Employer. MUSC does not discriminate on the basis of race, color, religion or belief, age, sex, national origin, gender identity, sexual orientation, disability, protected veteran status, family or parental status, or any other status protected by state laws and/or federal regulations. All qualified applicants are encouraged to apply and will receive consideration for employment based upon applicable qualifications, merit and business need. Medical University of South Carolina participates in the federal E-Verify program to confirm the identity and employment authorization of all newly hired employees. For further information about the E-Verify program, please click here: http://www.uscis.gov/e-verify/employees