Institution: Harvard Medical School
Location: Boston, MA
Category: Faculty – Science
Type: Full Time

The Harvard Medical School Curriculum Fellows Program (HMS CFP) welcomes applications for a Curriculum Fellow (CF) in Biomedical Informatics. The CFP is a postdoctoral service and training program focused on curriculum development, teaching, and educational programming in the biological and biomedical sciences. Curriculum Fellows are part of a larger cohort and work closely with members of the Harvard faculty and administration to develop, deploy, and evaluate evidence-based graduate training. Fellows also receive mentorship and career advising to support their development as educators and help them succeed in a variety of education-focused careers. More detailed information about the Curriculum Fellows Program, the role of a CF, and the outcomes of former fellows can be found in the 2022 CF cohort announcement available on our website (

The primary role of the CF in Biomedical Informatics will be support of the Master of Biomedical Informatics (MBI) program housed in the Department of Biomedical Informatics at Harvard Medical School. The MBI program is designed to advance the use of biomedical data, information, and knowledge for scientific inquiry, problem-solving, and decision-making. This program is created for students who are looking to develop skills in data science in the context of medicine and biological sciences to improve human health. It consists of two programs that enroll post-baccalaureate and post-doctoral students. Both programs include a range of foundational courses in quantitative and biomedical subjects and courses in emerging areas such as precision medicine, data science, and data visualization. All students complete a capstone research project with a Harvard faculty member.


  • Work with the MBI Program Director and faculty to expand the MBI curriculum and keep it current, including maintenance and updates of the MBI curriculum map
  • Provide instructional support to teaching faculty, including developing or identifying course-related content
  • Teach at least one introductory MBI course each year
  • Lead assessment and evaluation process of MBI courses and provide recommendations
  • Organize and participate in MBI Curriculum Committee meetings
  • Develop, implement, and support paracurricular activities, including symposia, workshops, and career development initiatives
  • Work with program leadership to ensure a fair and equitable admission process
  • Lead writing of manuscripts about educational research conducted as part of the role
  • Pursue additional opportunities to improve Biomedical Informatics education, including collaborations with other departments and affiliates
  • Mentor teaching assistants
  • Participate in strategic planning initiatives


  • An earned doctorate in a Biomedical Informatics-related field (i.e., computational biology, computer science, biostatistics, etc.)
  • Teaching experience at the graduate or undergraduate level

Qualified candidates will be evaluated based on their:

  • Demonstrated quantitative expertise and experience with biomedical data
  • Proficiency in either R or Python, preferably both
  • Familiarity with practices related to collaborative and reproducible scientific work
  • Ability to work collaboratively with multiple faculty and administrative partners to develop new courses and educational/training opportunities
  • Experience applying pedagogical best practices, including evidence-based teaching methods and technological innovations to the classroom
  • Ability to advise faculty on the application of evidence-based teaching practices to existing courses
  • Oral and written communication skills
  • Organizational and administrative skills and the ability to successfully plan and implement programs and events
  • Ability to work independently to identify and implement optimal solutions to diverse problems
  • Mentorship skills

Fellowships are intended for early-career scientist-educators. The CF appointment is renewable annually for a maximum of three years and is non-tenure-track. Fellows are appointed as Research Fellows and typically earn promotion to the rank of Lecturer during the term of the fellowship. The ideal start date for this position is approximately July 1, 2022. The current COVID-19 restrictions in place at Harvard Medical School mean this position may begin with a combination of remote and in-person work. However, fellows may be expected to work completely in person when this becomes possible. HMS and the CFP support flexible schedules, but these decisions will be made on an individual basis and will be regularly reviewed. Interviews for the MBI CF position will be held remotely.

The salary for this position will be highly competitive. Qualified candidates should expect compensation above the average post-doc salary in the Department of Biomedical Informatics.

To apply:

To apply, please send an email to containing the below list of application materials. Please address the email to Dr. Bradley Coleman, Director of the HMS Curriculum Fellows Program. Only complete applications submitted by the relevant deadline will receive a full review. The deadline to apply is April 8, 2022.

A cover letter that addresses your interest in and qualifications for the position.

  • A curriculum vitae.
  • A teaching statement following our Teaching Statement Guidelines. The teaching statement is an opportunity to describe your philosophy of teaching in the context of your own experiences. A discussion of diversity, equity and inclusion is an important component of the teaching statement.
  • The names and contact information of three professional references.

We are committed to cultivating an inclusive workplace culture of faculty, staff, and students with diverse backgrounds, styles, abilities, and motivations. We appreciate and leverage the capabilities, insights, and ideas of all individuals.

Harvard Medical School Mission and Community Values

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.