Assistant Member Tenure- Department of Machine Learning

Summary

Faculty member will develop and maintain an active research program in machine learning in oncology, primarily supported through extramural grants and publishing original research reports. The candidate will recruit and mentor research personnel, and participate collegially in the Center for Cancer Systems Genomics (CCSG) programs and the Moffitt Research Institute activities. This tenure‑track position focuses on independent research with a secondary teaching and mentorship role.

• Access to extensive retrospective and prospective patient data, including genomic, imaging, and patient‑reported information, as well as biospecimens from a large cohort.
• Collaboration with implementation scientists to integrate machine‑learning algorithms into electronic medical records and clinical workflows.
• Utilization of Moffitt’s state‑of‑the‑art computational resources, including a DGX‑A100/DGX‑H100/DGX‑H200 cluster.

• Expertise in artificial intelligence, decision‑support systems, machine and deep learning, and federated learning applied to cancer research.
• Outstanding record of collaborative research, especially in machine‑learning applications in healthcare.
• Experience in securing extramural funding, presenting at national and international conferences, and publishing in high‑impact peer‑reviewed journals.

• Maintain an integrated and/or independent research program in machine learning in oncology.
• Collaborate on multiple machine‑learning projects within Moffitt and externally.
• Engage in mentorship and service activities across Moffitt and affiliations.
• Contribute to current and future machine‑learning applications, including outcome modeling, human‑machine interaction, clinical decision support, information retrieval, radiomics, pathomics, and computational biology.

• Doctorate degree in computer science, engineering, physics, mathematics, statistics, or a related field with relevant research training.
• Academic rank beyond Assistant Member commensurate with experience and qualifications.
• Minimal expectations for formal teaching; focus primarily on research.

Salary ranges posted for this position represent the expected base pay range for the role. Actual compensation may vary based on location and job‑related factors such as experience, skills, education, and internal equity.

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

Comprehensive benefit package, relocation assistance, startup package, and research incentive plan.

Questions regarding the position should be directed to:
Issam El Naqa, PhD, FIEEE, Search Committee Chair, Department of Machine Learning (Issam.Elnaqa).

• Equal Employment Opportunity:
  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 inform us if you require accommodation.