Postdoc Fellow AI, Bioinformatics, Computational Biology, and Cancer Biomarker Discovery
Listed on 2026-07-26
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Research/Development
Data Scientist, Research Scientist, Clinical Research, AI Business & Operations
Moffitt Cancer Center, Tampa , Florida, US – Postdoc Fellow for AI, Bioinformatics, Computational Biology, and Cancer Biomarker Discovery Position Title Postdoc Fellow for AI, Bioinformatics, Computational Biology, and Cancer Biomarker Discovery Company Information
The Intelligent Cancer Omics and Immuno-Oncology (ICON) Lab, led by Dr. Xuefeng Wang, within the Department of Biostatistics and Bioinformatics at the H. Lee Moffitt Cancer Center—one of the nation’s top-ranked cancer research institutes is recruiting two postdoctoral fellows focusing on AI, Bioinformatics, Cancer Omics and Biomarker Discovery.
Duties and ResponsibilitiesThe fellow will contribute to cutting-edge projects leveraging artificial intelligence and advanced bioinformatics to drive innovation in cancer genomics and biomarker discovery. This position offers exceptional interdisciplinary training in both computational and translational oncology, providing direct access to high-performance computing infrastructure and rich collaborative resources across Moffitt's scientific community. The position is available immediately and will remain open until filled.
Position QualificationsThe Ideal Candidate:
- Research background/experiences in artificial intelligence, bioinformatics, biostatistics/statistics, computational biology, or genomics.
- A highly motivated and independent researcher with a strong quantitative scientific background.
- Prior experience in cancer genomics in not required, but a strong willingness and ability to learn new fields is highly desirable.
- Committed to producing high-quality, high-impact research and contributing to publications and grant proposals.
Responsibilities:
- Discover and validate new predictive biomarkers using large-scale cancer omics datasets, including single-cell and spatial omics data.
- Develop and extend computational, statistical and machine learning methods to advance cancer clinical and translational research.
- Design and implement novel visualizing tools to facilitate interpretation of complex omics results.
- Collaborate with clinicians and scientists across Moffitt clinical and research programs.
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