About the position
The Department of Epidemiology is strategically situated within the College of Public Health and Health Professions (PHHP) and the College of Medicine. Faculty members are jointly appointed to create synergies and collective strength, resulting in a competitive research profile and highly trained students who receive exceptional exposure to diverse expertise. Our faculty and students have received numerous national awards in research and mentoring and are committed to excellence in training. The department offers an epidemiology PhD, Master of Science, and concentration in the MPH program. It is also home to two National Institutes of Health Training grants (T32). Faculty members are strongly supported by our college-level instructional design team for course development and delivery and by our research core for grant development and submission. Dr. Jinling Liu's laboratory at the University of Florida's Department of Epidemiology and The Center for Genetic Epidemiology and Bioinformatics (GeneBio) is accepting applications for 1-2 fully-funded postdoctoral associate positions, starting immediately. Dr. Liu has extensive experience in big data analytics, systems biology, probabilistic graphical models, causal inference and machine learning. Dr. Liu's research interests lie in modeling the rapidly-accumulating big data in biology and medicine for precision medicine via a variety of statistical and machine learning techniques. The postdoctoral associates will be exposed to rich multi-omics data, a variety of diseases, advanced statistical and machine learning methods and wide collaborations with experts from different fields.
Responsibilities
- Multi-omics data analysis
- Novel method development and application
- Manuscript writing
- Research presentation at conferences
- Assistance with grant applications
- Student mentoring
Requirements
- PhD degree in computer science, statistics, biostatistics, biomedical informatics or related fields OR a PhD degree in biology or related fields
Nice-to-haves
- A strong background in programming (e.g., Python or R or C++)
- Research experience utilizing skills of programming, statistics, and AI
- Demonstrated independent and critical thinking abilities
- Good communication skills
- Prior research experience in analyzing biomedical data
Benefits
- Comprehensive health and leave benefits
- Access to libraries and other research resources
- Funds each training year to support professional development (e.g., travel to workshops or national conferences, purchase of education materials)
