Details
Title | Center for Computational Biomedicine Curriculum Fellow |
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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 (https://curriculumfellows.hms.harvard.edu/ ). 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:
Additionally, the CCB Curriculum Fellow will also have specific responsibilities to the CFP:
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. Qualified candidates will be evaluated based upon their:
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 [email protected] to alert the hiring team that you’ve applied. To apply, CLICK HERE , or copy the application URL into your browser: https://academicpositions.harvard.edu/postings/13514 Below are the required application materials needed to apply:
If you have any questions specific to the program or fellowship, please email: [email protected] . |
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 | [email protected] |
Equal Opportunity Employer | We are committed to cultivating an inclusive workplace culture (https://hr.fas.harvard.edu/inclusive-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: https://hms.harvard.edu/about-hms/campus-culture/mission-community-values-diversity-statement 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 |
Keywords | 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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