Pre-Doctoral Fellow, Radiation Oncology

The General Hospital Corporation; Boston (MA); On-site; USD 42,000 - 60,000; Full time

Job summary

Mass General Brigham invites applications for a Predoctoral Research Fellow in Artificial Intelligence. The role focuses on applied AI/deep learning to create and evaluate algorithms using clinical data across oncology and cardiology, including imaging and EHR analysis.

Under the PI's supervision, you will design independent experiments, publish findings, and receive mentorship within the AIM program, in a 5-year appointment framework. Onsite work at 221 Longwood Avenue, Boston.

Qualifications

• Bachelor's degree in a related field is required.
• Master's degree in data sciences, CS, physics, or related field preferred.
• Concurrent enrollment in a PhD program is expected.

Responsibilities

• Work with the AIM program to develop AI methods for clinical tasks such as oncology and imaging.
• Participate in R&D projects under supervision and PI direction.
• Develop analysis plans with AIM scientists and validate AI technologies.
• Publish results in peer‑reviewed journals and present at conferences.

Skills

Data science

Deep learning

Research design

Analytical skills

Time management

Presentation skills

Education

Bachelor's Degree Related Field of Study

Master's degree in Data Sciences, Computer Science, Physics, or related field

Concurrent enrollment in an established PhD program

Job description

Site: The Brigham and Women's Hospital, Inc.

Mass General Brigham relies on a wide range of professionals, including doctors, nurses, business people, tech experts, researchers, and systems analysts to advance our mission. As a not-for-profit, we support patient care, research, teaching, and community service, striving to provide exceptional care. We believe that high-performing teams drive groundbreaking medical discoveries and invite all applicants to join us and experience what it means to be part of Mass General Brigham.

Job Summary

Predoctoral Research Fellow in Artificial Intelligence

The Predoctoral Research Fellow conducts research in the area of applied Artificial Intelligence/Deep Learning to develop and evaluate algorithms leveraging clinical data (e.g. imaging, electronic health record, pathology, genomics) for several medical fields, including oncology and cardiology. Projects may include the application of deep learning methods to tumor phenotype on serial medical imaging and patient-specific characteristics such as identifying imaging phenotype of co-morbid illnesses (e.g. lung and cardiac disease) and treatment side effects. Additional projects could include automated segmentation for radiation therapy and implementation of existing algorithms into the clinic. The Fellow is a member of the team at the Mass General Brigham (MGB) Artificial Intelligence in Medicine (AIM) program (aim.hms.harvard.edu) and is expected to conduct research leading to peer-reviewed publications and presentations at international meetings with guidance from our faculty.

Under the supervision of the Principal Investigator, the Fellow carries out and designs highly sophisticated and independent experiments. The Fellow is allowed to and encouraged to publish the results of their research or scholarship and receive credit for such during the appointment period. The Fellow receives training, professional development, and mentorship during the appointment period. The appointment is time-limited and should be for a term of no longer than 5 years.

Duties & Responsibilities

1. Working alongside the team in the Artificial Intelligence in Medicine (AIM) Program, develop AI methods specific for clinical tasks, including but not limited to oncology and imaging.
2. Participate in research and development projects under supervision and direction of the Principal Investigator.
3. Develop analysis plans for the defined projects with support from the scientists within AIM.
4. Evaluate the performance of AI technologies in independent validation cohorts.
5. Present results at national and international conferences.
6. Publish results in peer-reviewed manuscripts.

Education

• Bachelor's Degree Related Field of Study required.
• Master's degree in Data Sciences, Computer Science, Physics, or related field preferred.
• Concurrent enrollment in an established PhD program.

Experience

• Preferably 1-2 years of experience with Artificial Intelligence/Deep Learning techniques and analyses, with a track record of scholarship in these fields.
• Demonstrated interest in the application of computational techniques to medical imaging.

Knowledge, Skills and Abilities

• Strong data science/computer science background with skills and experience in deep learning preferred.
• Strong research design and analytical skills.
• Strong database statistical skills.
• In-depth knowledge of field of research.
• Excellent time management/organizational skills.
• Strong written and verbal presentation skills.

The Fellow will work in a laboratory space dedicated to the AIM program with additional potential to establish successful project-specific collaborations in a variety of directions.

Additional Job Details (if applicable)

Remote Type

Onsite

Work Location

221 Longwood Avenue

Scheduled Weekly Hours

40

Employee Type

Regular

Work Shift

Day (United States of America)

Pay Range

$41,932.80 - $60,340.80/Annual

Grade

5

Pay Details and Benefits

At Mass General Brigham, we believe in recognizing and rewarding the unique value each team member brings to our organization. Our approach to determining base pay is comprehensive, and any offer extended will take into account your skills, relevant experience if applicable, education, certifications and other essential factors. The base pay information provided offers an estimate based on the minimum job qualifications; however, it does not encompass all elements contributing to your total compensation package.

In addition to competitive base pay, we offer comprehensive benefits, career advancement opportunities, differentials, premiums and bonuses as applicable and recognition programs designed to celebrate your contributions and support your professional growth.

EEO Statement: 2200 The Brigham and Women's Hos