Assistant/Associate Member


Bioinformatics Faculty Position
• Collaborate on a variety of cancer clinical and basic science research projects.
• Communicate clearly and openly.
• Build relationships to promote a collaborative environment.

The Department of Biostatistics and Bioinformatics at Moffitt Cancer Center, a National Cancer Institute-designated Comprehensive Cancer Center, is seeking a faculty member in the tenure-earning rank of Assistant/Associate Member with preference for strong expertise in bioinformatic analysis of high-throughput sequencing data. Moffitt is affiliated with the University of South Florida and a University appointment is available in the rank of Assistant/Associate Professor as applicable. Methodological research in bioinformatics is also expected.
The Department currently has 13 faculty and approximately 27 staff engaged in a wide range of statistical and bioinformatics research and collaborations on clinical and biological studies in cancer including novel therapeutic and drug discoveries, prognostic and predictive biomarker developments, chemoprevention, high throughput genomics, proteomics, next-generation sequencing data-based investigations, epidemiological studies, comparative effectiveness research, clinical trial designs, and personalized medicine studies. Many of these projects draw upon Moffitt’s Total Cancer Care initiative, which provides access to a comprehensive set of clinical and molecular data on a large number of cancer patients.


Successful candidates must have a Ph.D. in biomedical informatics, bioinformatics, computer science or related field and relevant research training and experience.
The Ideal Candidate:
• We seek candidates who can contribute to the many current clinical and basic science studies at Moffitt, as evidenced by a history of peer-reviewed publications and involvement in grant supported research projects.
•Preference will be given to applicants with an outstanding record of team science or collaborative bioinformatics with an emphasis in high-throughput sequencing, single-cell sequencing, and quantitative sequencing approaches (e.g., ChIP-seq, TT-seq, and ATAC-seq). Additional interest in application of cutting-edge sequencing analysis methods to cancer in order to understand novel DNA/RNA characteristics is beneficial.
•The candidate is expected to identify methodological issues that arise in collaborative research and engage in independent, methodological

Start date

As soon as possible

How to Apply
The reference number is 26325


Jamie Teer