About this role
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Job Title
Postdoctoral Scholar – Genetic Epidemiology and AI for Complex Diseases
Department
Medicine | Ophthalmology
The Department of Ophthalmology and Visual Sciences at The Ohio State University is seeking a highly motivated Postdoctoral Scholar to pursue advanced research training under the mentorship of Dr. Raymond Gao. The successful candidate will collaborate on the design and execution of innovative research focused on large-scale genetic and genomic data analysis, genetic risk prediction, and the development and application of artificial intelligence (AI) and machine learning (ML) approaches to study complex human diseases, including glaucoma and Alzheimer's disease.
Responsibilities include analyzing and interpreting large-scale genetic, genomic, and phenotypic datasets, such as biobank, cohort, and genome-wide association study (GWAS) data; developing and evaluating genetic risk prediction models, including polygenic risk scores; applying AI and ML methods to integrate genetic and clinical data for disease risk prediction; preparing manuscripts for publication in peer-reviewed journals and presenting findings at scientific conferences; contributing to the development of grant proposals for state and federal funding opportunities; and developing, adopting, and implementing novel analytical and computational methods to advance biomedical research.
Minimum qualifications
PhD (or equivalent doctoral degree) in genetic epidemiology, statistical genetics, biostatistics, bioinformatics, computational biology, computer science, or a related field, either completed or expected before the start date. Requires successful completion of a background check; qualified candidates may be asked to complete a pre-employment physical, including a drug screen.
Preferred qualifications
Experience analyzing large-scale genetic data (e.g., GWAS, sequencing, or biobank data such as UK Biobank or All of Us); familiarity with polygenic risk score methods; programming skills in R and/or Python; experience with tools such as PLINK and with high-performance computing; working knowledge of machine learning or deep learning frameworks; and a strong record of, or clear potential for, first-author publications.
Additional Information
Location
Pelotonia Research Center (1040)
Position Type
Term (Fixed Term)
Scheduled Hours
40
Shift
First Shift
Final candidates are subject to successful completion of a background check. A drug screen or physical may be required during the post offer process.
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