UNIV - Assistant Professor, Division of Biomedical Informatics and AI - Department of PHS

Healthcare
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • PhD, MD, MD/PhD, or equivalent degree in relevant fields such as biomedical informatics or computational biology.
  • Proven expertise in large-scale genetic and genomic analyses, including GWAS and pharmacogenomics.
  • Experience with EHR-linked biobanks and real-world clinical data integration.
  • Demonstrated ability to develop or apply AI/ML methods to healthcare and genomic data.
  • Evidence of research productivity and potential for acquiring independent funding.
  • Strong commitment to teaching, mentoring, and interdisciplinary collaboration.

Responsibilities

  • Establish and lead an independent, funded research program in bioinformatics and precision medicine.
  • Conduct pioneering research using EHR-linked biobanks and genomic datasets to explore health outcomes.
  • Develop advanced statistical and machine learning methods for genomic and health data analysis.
  • Collaborate on studies involving GWAS, pharmacogenomics, and genetic epidemiology.
  • Work with multidisciplinary teams across MUSC to promote interdisciplinary research.
  • Support institutional initiatives in precision medicine and AI-driven healthcare advancements.
  • Engage in teaching and mentoring activities in relevant educational programs.

Benefits

  • Competitive start-up package with dedicated research space.
  • Access to core facilities and resources for research development.
  • Administrative support for grant writing and funding acquisition.
  • Opportunities for mentorship and professional development through interdisciplinary collaboration.
Full Job Description
Job Description 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

Pay Range
0.00 - 0.00 - 0.000

Scheduled Weekly Hours
40

Work Shift

Job Description

Job Description:

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.

Additional Job Description
Physical Requirements: (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!

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