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Postdoctoral Fellow for Computational Oncology and AI in Cellular Immunotherapy and Immuno-Oncology

Moffitt Cancer Center

Working at Moffitt is both a career and a mission: to contribute to the prevention and cure of cancer. Moffitt is a National Cancer Institute-designated Comprehensive Cancer Center, the only one based in Florida, and employs a dedicated team of nearly 11,000. Moffitt has been recognized as a Best and Brightest Company to Work For in the Nation and named among 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, is recruiting a Postdoctoral Fellow. 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 interdisciplinary training in both computational and translational oncology, with supervision provided jointly by the Department of Biostatistics & Bioinformatics, Department Blood and Marrow Transplant and Cellular Immunotherapy, and the Moffitt Immuno‑Oncology Program. The position is available immediately and will remain open until filled. Ideal Candidate Research background/experiences in artificial intelligence, bioinformatics, biostatistics, computational biology, or genomics. A highly motivated and independent researcher with a strong quantitative background. Strong willingness and ability to learn new fields, including cancer genomics. Commitment 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 clinical and translational research. Design and implement novel visualization tools to facilitate interpretation of complex omics results. Collaborate with clinicians and scientists across Moffitt clinical and research programs. Qualifications Required: PhD in Bioinformatics, Computer Science, Computational Biology, Statistics/Biostatistics, Data Science, or related quantitative fields. Strong programming skills in Python and R. Research background in AI and machine learning. Experience processing and integrating multi‑omics data, including single‑cell RNA‑seq and spatial omics. Excellent communication and writing skills. Application Send a single PDF file that includes a cover letter summarizing your research training and accomplishments, your current CV with recent publications, and contact information of at least two references to View email address on click.appcast.io . 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. 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, personal, and professional experience have prepared them to contribute to our commitment to diversity and excellence. Reasonable Accommodation Federal law requires employers to provide reasonable accommodation to qualified individuals with disabilities. Please let us know if you require a reasonable accommodation to apply for a job or to perform your job. Contact the Human Resources receptionists by phone at View phone number on click.appcast.io or by email at View email address on click.appcast.io for accommodation requests. This contact information is for accommodation requests only and cannot be used to inquire about the status of applications. #J-18808-Ljbffr Moffitt Cancer Center

Vacancy posted 1 day ago
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