Postdoctoral Fellow – Machine Learning/FAIR and Explainable Machine Learning

At Moffitt Cancer Center, we strive to be the leader in understanding the complexity of cancer and applying these insights to contribute to the prevention and cure of cancer. Our diverse team of over 9,000 are dedicated to serving our patients and creating a workspace where every individual is recognized and appreciated. For this reason, Moffitt has been recognized on the 2023 Forbes list of America’s Best Large Employers and America’s Best Employers for Women, Computerworld magazine’s list of 100 Best Places to Work in Information Technology, DiversityInc Top Hospitals & Health Systems and continually named one of the Tampa Bay Time’s Top Workplace. Additionally, Moffitt is proud to have earned the prestigious Magnet® designation in recognition of its nursing excellence. Moffitt is a National Cancer Institute-designated Comprehensive Cancer Center based in Florida, and the leading cancer hospital in both Florida and the Southeast. We are a top 10 nationally ranked cancer center by Newsweek and have been nationally ranked by U.S. News & World Report since 1999.
Working at Moffitt is both a career and a mission: to contribute to the prevention and cure of cancer. Join our committed team and help shape the future we envision.

Summary

We are seeking a motivated and creative postdoctoral researcher with background in machine learning and system informatics to join the team of Dr. Yi Luo. Our current research focuses on FAIR (findable, accessible, interoperable, and reusable) and explainable machine learning and their application for health outcomes, clinical decision support, and credible models in precision medicine, health equity, and healthcare quality. Our research areas mainly include: 1) bias control, causal inference, and contribution analysis; 2) individual cancer patients’ treatment outcomes prediction and clinical decision support; 3) human-in-the-loop approach for physician-machine interface design; 4) developing and using system informatics to study health disparities. If your background overlaps and you are interested in working on one or more of these areas, we encourage you to apply. We have exciting opportunities for you within our team at the institution that will strongly support your scientific growth and future successes.

The FAIR and explainable machine learning group in the Machine Learning Department at Moffitt combines multidisciplinary and multiscale approaches from the fields of cancer biology, bioethics, computer science, decision science, medical physics, and health services research to improve cancer prevention and treatment. So far, we are collaborating with clinical and research investigators from the programs of Anesthesiology, Breast Oncology, Cancer Epidemiology, Malignant Hematology, Radiation Oncology, and Thoracic Oncology in Moffitt Cancer Center. Also, we actively collaborate with the extramural oncology centers and academic institutions.

To learn more about our exciting work being done visit: http://lab.moffitt.org/LUO

Position Highlights: 

• Moffitt integrates excellent patient care with cutting-edge clinical and basic research. Having a cancer hospital on-site provides unique opportunities for translational research.
• The position is essential for development of comprehensive tools benefiting basic to clinical research through exploring explainable biophysical pathways from retrospective datasets.
• The position offers vibrant and interactive work environment in the Quantitative Science Division and results will bring value beyond the community of Moffitt patients.
• You will be encouraged and supported to apply for training grants.
• Outstanding mentorship from expert faculty with wide-ranging funded research programs including T32 Training Grants.

The Ideal Candidate:

• Deep knowledge of explainable/credible machine learning, probabilistic graphical models, reinforcement learning, and causal inference or system informatics, human-machine interface, sequential decision making, and agent-based modeling.
• High motivation and desire to be part of multidisciplinary group, good work ethic.
• Excellent interpersonal and communication skills (written and verbal).
• Proficiency with programming languages, applications, and optimization, simulation, statistical packages.
• Experience with extraction, handling, and processing of large electronic health record data.
• Preferable knowledge of cancer biology.

Responsibilities:

• Data preparation, organization, management, and analysis.
• Development of new and tuning of existing machine learning and analytical approaches.
• Presentation of data and results in a clear and concise manner.
• Active participation in the group meetings and meetings with the collaborating teams.
• Ability to work with the team and independently.
• Supervision of undergraduate and graduate students.
• Preparation of grant applications, publications, and presentations.
• Meeting project goals.

Credentials and Qualifications:

• Ph.D. degree and research experience in the fields of machine learning and/or systems and industrial engineering in biomedical applications.
• At least one first Author publication.

Moffitt Postdocs are provided free employee-only Medical and eligible for Dental, Vision, Paid Time Off, Retirement, Parental Leave and more. With a move to Tampa, you may be eligible for relocation allowance per policy. Reason to relocate, aside from the sunshine, beaches and year-round outdoor recreation associated with the Gulf Coast of Florida, Tampa is a thriving metropolitan city with unique cultural attractions, low cost of living and a high quality of life. We strive for work/life balance.

If you have the vision, passion, and dedication to contribute to our mission,

then we have a place for you.

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 for three references to Dr. Yi Luo (Yi.Luo@moffitt.org).