SUBSPECIALTY ACADEMIC RADIOLOGISTS W/ PROF. DEVEL. IN ARTIFICIAL INTELLIGENCE & BIG DATA ANALYTICS
Brigham and Women's Hospital
Application
Details
Posted: 01-Jun-23
Location: Boston, Massachusetts
Type: Full Time
Subspecialties:
Breast Radiology
Chest Radiology
Emergency Radiology
Gastrointestinal Radiology
Ultrasound
Internal Number: 888999
The Department of Radiology at Brigham and Women’s Hospital (BWH) is seeking academically promising, full-time, board-certified or board-eligible radiologists interested in combining subspecialty radiology clinical practice with specific training in Artificial Intelligence (A.I.) and Big Data Analytics. Academic appointment at the Instructor, Assistant Professor, or Associate Professor level at Harvard Medical School (HMS) will be commensurate with experience. We seek to recruit academically promising faculty into many divisions, specifically Breast Imaging, Thoracic Imaging, Abdominal/Ultrasound Imaging and Emergency Radiology, beginning July 1, 2024.
Candidates are expected to contribute to and advance the patient care, research, and educational missions of their Academic Division and HMS. Faculty will typically have one day per week of protected academic time. They will be enrolled in the fall term Harvard Extension School online course “Big Data and Machine Learning in Healthcare Applications” and will receive an additional day of protected academic time/week for the duration of this course, which runs from September to December. (Basic knowledge of Python is required for this online course. For applicants not familiar with Python, there will be an internal preparation class, which will take place during their academic day in July/August). For the remainder of the first academic year, the faculty will spend 3.5 days/week on the chosen subspecialty clinical service with the remaining 1.5 days dedicated to an A.I. or Data Analytics project, related to their division, with mentorship and oversight provided by the Division Chief and Oleg Pianykh, Ph.D., Director of Medical Analytics Group, Massachusetts General Brigham (MAG.MGB ) and/or Kathy Andriole, Ph.D, Director of Academic Research and Education, MGB Data Science Office (datascience.massgeneralbrigham ). At the beginning of the second year of appointment, faculty will typically have one day per week of protected academic time with 4-days per week on clinical service which can be adjusted based on additional extramural funding. Compensation is equivalent to other full-time faculty in the department, primarily based on years in practice and academic rank.
Located in the thriving Boston metropolis, The Department of Radiology at BWH is a member of Mass General Brigham Integrated Healthcare system, comprised of 2 renowned academic medical centers and 10 specialty and community hospitals. It has connections to biotech and the broad scientific community within Harvard Medical School and Massachusetts Institute of Technology, providing ample opportunities for innovative research and teaching. Additional benefits to living in this vibrant, resourceful and culture-rich environment include excellent public-school systems, easy access to both the ocean and the mountains, and at-home workstations to support work-life balance. The department has a robust education and research portfolio including 42 residents and 65 subspecialty fellows providing clinical services at Brigham and Women’s Hospital, Dana Farber Cancer Institute and Brigham and Women’s Faulkner Hospital.
The BWH Department of Radiology is committed to ensuring our diverse community feels welcome, cared for, and valued. Candidates who have experience working with diverse range of faculty, staff and patients, and who can contribute to the climate of inclusivity are encouraged to identify their experiences in these areas.
We are an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions or any other characteristic protected by law. Interested candidates should send a cover letter and CV via e-mail to Fiona Fennessy MD PhD at ffennessy@bwh.harvard.edu