Moffitt Cancer Center, the top-ranked NCI-designated comprehensive cancer center in the Southeastern United States, is seeking a faculty member to lead a new Department within the Division of Quantitative Sciences focused on the development and application of machine learning techniques across the spectrum of cancer research, with an initial emphasis on biomedical imaging analytics. This position offers an exciting opportunity to build upon Moffitt’s significant data and analytics assets, accelerating scientific discovery and translation to the clinic.
The Division of Quantitative Sciences at Moffitt Cancer Center is seeking a senior faculty member with expertise in machine learning, success in obtaining peer reviewed funding and strong leadership skills to chair a new Department of Machine Learning and Biomedical Imaging. To build upon Moffitt’s strong foundation in biomedical imaging informatics, candidates with research interests related to radiomics and/or pathomics are preferred. The Division of Quantitative Sciences currently includes the Department of Biostatistics and Bioinformatics and the Department of Integrated Mathematical Oncology, housing more than 20 faculty and 40 staff members engaged in a wide range of statistical and mathematical modeling, bioinformatics, and informatics research and collaborations on clinical and biological studies in cancer, including novel therapeutic and drug discoveries, prognostic and predictive biomarker developments, chemoprevention, high throughput genomics, proteomics, next-generation sequencing data-based investigations, epidemiological studies, comparative effectiveness research, patient reported outcomes, clinical trial designs, and personalized medicine studies.
Moffitt Cancer Center’s Department of Radiology, recently ranked among the top cancer centers for NIH awards by the Academy for Radiology and Biomedical Imaging Research, offers an intellectually stimulating environment for faculty to develop and apply image-computing solutions to highly translational and clinically relevant problems in oncology. The 37 clinical faculty housed within the Department of Radiology, are actively engaged in research related to image analytics and extracting segmented images at the point of care, with enthusiasm for scientific team collaboration. Moffitt’s Department of Pathology includes an esoteric lab with a full suite of advanced capabilities in a CLIA environment, including AQUA and multispectral quantitative imaging. Moffitt also has a variety of Shared Resources to support basic and applied research, including the Imaging Response and Assessment Team (IRAT) Core and a high performance computing facility.
Endless opportunities to link quantitative imaging data with clinical and molecular data are possible with Moffitt’s enterprise wide data warehouse, the Health and Research Informatics (HRI) Platform. HRI currently houses information on more than 500,000 unique patients, including treatment information available from the electronic health records and Cancer Registry on more than 200,000 cancer patients, patient-reported data on 150,000 patients, and vast amounts of research and clinical Research Information Exchange Network (ORIEN), a collaboration involving more than 14 academic cancer centers across the country, of which Moffitt is a founding member.
The Chair is expected to lead an independent research program, leveraging Moffitt’s vast data resources to accelerate discoveries across the basic, clinical and population sciences at Moffitt Cancer Center. Moffitt is affiliated with the University of South Florida, with collaborative opportunities in the Department of Computer Science and Engineering. A University appointment is available in the appropriate rank as applicable. Methodological research in informatics is also expected.
The Ideal Candidate:
We seek candidates who can lead the new Department, as well as his or her own independent research program in machine learning, as evidenced by a history of peer-reviewed publications and involvement in grant supported research projects.
Preference will be given to applicants with an outstanding record conducting team science with experience in biomedical imaging, computational imaging, radiomics, pathomics, and machine learning as it applies to oncology.
Strong leadership skills are required to set vision for the new Department and execute upon that vision.
Set vision for the new Department.
Recruit and mentor faculty with expertise in machine learning.
Build relationships to promote a collaborative environment across the research and clinical enterprise.
Communicate clearly and effectively.
Maintain a rigorous extramurally funded research program.
Credentials and Qualifications:
Successful candidates must have an MD or Ph.D. in biomedical informatics, biomedical engineering, computer science, imaging science, electrical engineering or related field and relevant research training and experience in machine learning techniques applied to oncology.
Academic rank beyond Associate Member will be commensurate with experience and qualifications. Appointment at the Associate or Senior Member rank requires a minimum of five years of experience at the Assistant or Associate Member level, respectively. The position is tenure-earning. Salary is competitive with similar institutions.