Postdoctoral Fellow for Computational Biology, Cancer Genomics and Biomarker Discovery

Working at Moffitt is both a career and a mission: to contribute to the prevention and cure of cancer.

As the only National Cancer Institute-designated Comprehensive Cancer Center based in Florida, Moffitt employs some of the best and brightest minds from around the world. Join a dedicated team of nearly 11,000 who are shaping the future we envision. Moffitt has been recognized as a Best and Brightest Company to Work For in the Nation and is continually named one of the Tampa Bay Times’ Top Workplaces.

Summary

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—an NCI-designated Comprehensive Cancer Center and one of the nation’s top-ranked cancer research institutes—is recruiting a Postdoctoral Fellow. Position Highlights: The 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. The 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. Credentials and Qualifications: Required: PhD in Bioinformatics, Computer Science, Computational Biology, Statistics/Biostatistics, Data Science, or related quantitative fields. Preferred:
• Strong programming skills in languages such as Python and R.
• Research background in AI and machine learning.
• Experience of processing and integration of multi-omics data including single-cell RNA-seq, spatial omics, etc.
• Excellent communication and writing skills. How to Apply: Interested applicants should send a single PDF file that includes a cover letter summarizing their research training and accomplishments, current CV with recent publications, and contact information of at least two references to xuefeng.wang@moffitt.org. Informal inquiries are also welcome.
  
  

Salary Range

Salary ranges posted for this position represent the expected base pay range for the role. Actual compensation may vary based on location and a variety of job-related factors, including experience, skills, education, and internal equity among Team Members in similar positions.

We are committed to maintaining fair and equitable pay practices and regularly review compensation to ensure alignment across our workforce.

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• Equal Employment Opportunity
  
  

Moffitt Cancer Center is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, or protected veteran or disabled status. We seek candidates whose skills, and personal and professional experience, have prepared them to contribute to our commitment to diversity and excellence.

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