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Harvard University Center for Computational Biomedicine Curriculum Fellow in Cambridge, Massachusetts


Title Center for Computational Biomedicine Curriculum Fellow

School Harvard Medical School

Department/Area Center for Computational Biomedicine (CCB)

Position Description

The Harvard Medical School Curriculum Fellows Program ( HMS CFP ) welcomes applications for a Curriculum Fellow (CF) for the Center for Computational Biomedicine ( CCB ). This postdoctoral program targets early-career scientist-educators, emphasizing curriculum development, teaching, and educational programming in the biological and biomedical sciences.

The CCB Curriculum Fellow collaborates with a diverse cohort of Curriculum Fellows, leveraging individual expertise while closely engaging with Harvard Medical School faculty and administration to craft, implement, and assess evidence-based graduate training. Fellows benefit from mentorship and career guidance, nurturing their growth as educators and facilitating success across various education-focused careers. Further details are available on our website ( (

The CCB develops shared data and analytic resources that broadly serve HMS . This includes a strong educational mandate for courses and skills related to software, data analysis, technical computational skills and the adoption of new methods (eg AI/ML, single cell RNA -seq, etc). The CCB CF will be responsible for developing curricula for CCB workshops offered to HMS graduate students and postdocs across HMS programs and departments.

The CCB CF will report directly to the CCB Director, Dr. Robert Gentleman and will receive one-on-one mentorship from Dr. Gentleman, the Director of the CFP , Dr. Aimee Hollander and senior members of CCB .

The primary responsibilities of the CCB Curriculum Fellow are expected to include:

  • Serving as the liaison between the CCB and other HMS departments to identify educational gaps that can be addressed by the CCB

  • Surveying HMS faculty, students, and postdoctoral fellows to identify gaps in education and needs that the CCB can address across HMS departments

  • Curriculum development for CCB workshops in computational biology and machine learning

  • Delivering hands on training and office hours for workflows in computational biology

  • Using and developing curricula using AI/ML models and approaches for CCB -hosted workshops and other training offerings

  • Lead and intellectually contribute to one of CCB’s scholarship of teaching and learning projects with the expectation that findings collected during the fellowship will be presented at conferences and/or published in a scientific/education journal

    Additionally, the CCB Curriculum Fellow will also have specific responsibilities to the CFP :

  • Take required courses including Teaching 100 and Teaching 101.

  • Participate in weekly CFP group meetings and pedagogical journal clubs.

  • Present at university-wide workshops on curricular and pedagogical topics.

  • Assist in developing the curriculum for the NIH -mandated Responsible Conduct of Science ( RCOS ) course.

  • Assist with the organization of the Graduate Science Education Series ( ( GSES ),


Candidates are expected to have a PhD in Computational Biology, or closely related field and 0-3 years of postdoctoral research/fellowship experience. Candidates who are currently finishing their doctoral work but have not yet graduated are encouraged to apply.

Qualified candidates will be evaluated based upon their:

  • Demonstrated interest or experience with teaching and/or curriculum development in higher education settings.

  • Comfort and experience teaching and developing curriculum in an asynchronous online environment.

  • Organizational and written and oral communication skills.

  • Ability to support collaborations across departments in a fast-paced academic environment.

    Application instructions:

The ideal start date for this Curriculum Fellow is as early as July 1st, 2024. This is a hybrid position and the candidate will be expected to work in person on the HMS campus in Boston, MA 3 days per week. The CF appointment is renewable annually for a maximum of three years and is non-tenure-track.

Applications are being reviewed on a rolling basis. Once you apply through the portal, please email to alert the hiring team that you’ve applied.

To apply, CLICK HERE ( , or copy the application URL into your browser:

Below are the required application materials needed to apply:

  • A cover letter that addresses your interest in and qualifications for the position. Please highlight your research interests and skills.

  • A curriculum vitae.

  • A teaching statement. 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. Submissions will be evaluated according to the guidelines found on our website, here ( ,

  • The names and contact information of three professional references.

If you have any questions specific to the program or fellowship, please email:

Basic Qualifications

Candidates are expected to have a PhD in Computational Biology, or closely related field and 0-3 years of postdoctoral research/fellowship experience. Candidates who are currently finishing their doctoral work but have not yet graduated are encouraged to apply.

Additional Qualifications

Special Instructions

Contact Information

Bethany Krevat

Curriculum Fellows Program Coordinator

Contact Email

Equal Opportunity Employer

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.

Minimum Number of References Required 3

Maximum Number of References Allowed 3


artificial intelligence, machine learning, data, data science, computational biology, biomedicine, biology, biomedical science, data, science, curriculum, teaching, faculty, postdoc, genetics, neurology, neurobiology, neuroscience

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