Translational Bioinformatics Scientist (Genomics & AI)

Medical University of South Carolina (MUSC); Charleston (SC); On-site; USD 95,000 - 130,000; Full time

Benefits offered by this job

Competitive start-up package

Job summary

The Medical University of South Carolina (MUSC) invites applications for a full-time Assistant Professor in Translational Bioinformatics. The role focuses on leveraging large-scale genomic and health data to advance precision medicine and human health.

Ideal candidates will integrate multimodal data (genomics, transcriptomics, clinical data) and apply AI/ML methods. Start-up support and collaboration across MUSC are available to accelerate impactful research and training.

Qualifications

• PhD, MD, MD/PhD or equivalent in biomedical informatics or related field.
• Expertise in large-scale human genetic and genomic analyses (GWAS, PheWAS).
• Experience with EHR-linked biobanks and real-world clinical data.
• Evidence of AI/ML methods applied to genomic/health data.
• Proven research productivity and potential for funding.
• Commitment to teaching, mentoring and collaboration.

Responsibilities

• Develop an independent, funded translational bioinformatics program.
• Leverage EHR-linked biobanks and large genomic datasets to study disease, therapy, and outcomes.
• Apply advanced statistical, computational, and AI/ML methods to diverse biomedical data.
• Lead studies in GWAS, PheWAS, fine-mapping, and polygenic risk; collaborate across MUSC.
• Mentor students and trainees; contribute to interdisciplinary research initiatives.
• Support precision medicine and genomics initiatives through service and education.

Skills

Genomics analyses

GWAS

PheWAS

AI/ML methods

EHR-linked biobanks

Multimodal data integration

Education

PhD in biomedical informatics or related field

Tools

R

Python

Statistical genetics software

Job description

The Medical University of South Carolina (MUSC) invites applications for a full-time Assistant Professor in Translational Bioinformatics. The role focuses on leveraging large-scale genomic and health data to advance precision medicine and human health.

Ideal candidates will integrate multimodal data (genomics, transcriptomics, clinical data) and apply AI/ML methods. Start-up support and collaboration across MUSC are available to accelerate impactful research and training.