Post Doctoral Scholar

The Postdoctoral Researcher will contribute to advanced research in fracture risk assessment using genomic data and machine learning under the supervision of Dr. Qing Wu in the Department of Biomedical Informatics. The researcher will be involved in the development of personalized risk models for osteoporotic fractures, focusing on minority populations. Responsibilities include developing and optimizing machine learning algorithms, analyzing multi-omics data (genomic, phenotypic), and contributing to the validation of precision medicine tools. The position also includes collaborating with internal and external partners, contributing to grant writing, and disseminating research through publications and conferences.

Supervisory Responsibilities
Non-Supervisory Professional Staff: None
Students: May assist in mentoring graduate students

Educational Requirements
Minimum Education Requirements: Ph.D. in Bioinformatics, biomedical informatics Biostatistics, Computer Science, or related fields with a strong quantitative focus.
Desired Education: Training or experience in genomics or precision medicine.

Skills Required/Desired:
Proficiency in programming languages such as Python, R, or MATLAB.
Experience with machine learning and big data analysis.
Knowledge in genomics, genetics, or multi-omics data analysis is strongly preferred.
Ability to contribute to grant writing and research publications.
Experience with healthcare disparities research is a plus.

Final candidates are subject to successful completion of a background check. A drug screen or physical may be required during the post offer process.