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美國(guó)哈佛醫(yī)學(xué)院2024年招聘博士后職位(計(jì)算生物醫(yī)學(xué)中心課程研究員)

時(shí)間:2024-06-06來(lái)源:中國(guó)博士人才網(wǎng) 作者:佚名

美國(guó)哈佛醫(yī)學(xué)院2024年招聘博士后職位(計(jì)算生物醫(yī)學(xué)中心課程研究員)

哈佛醫(yī)學(xué)院(Harvard Medical School,簡(jiǎn)稱:HMS)是世界上最頂尖的醫(yī)學(xué)院,它因高超的醫(yī)學(xué)技術(shù)與每年錄取的學(xué)生最少而聞名世界。與商學(xué)院,法學(xué)院共同占有世界高等學(xué)術(shù)殿堂的一席地位。學(xué)院每年錄取的國(guó)際學(xué)生極少極少,這樣保證了學(xué)生的質(zhì)量。

Harvard Medical School Center for Computational Biomedicine Curriculum Fellow

Harvard Medical School

Job 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:

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), https://curriculumfellows.hms.harvard.edu/graduate-science-education-series

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:

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.

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.

Application instructions:

This position is open until filled, and the starting date for the position is ideally as soon as possible. Applications are being reviewed on a rolling basis. Once you apply through the portal below, please email cfp@hms.harvard.edu to alert the hiring team that you’ve applied.

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, https://curriculumfellows.hms.harvard.edu/teaching-statement-guidelines

- The names and contact information of three professional references.

If you have any questions specific to the program or fellowship, please email: cfp@hms.harvard.edu.

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.

Harvard Medical School strives to cultivate an environment that promotes inclusiveness and collaboration among students, faculty and staff and to create new avenues for discussion that will advance our shared mission to improve the health of people throughout the world.

Contact Information:

Bethany Krevat

cfp@hms.harvard.edu

Center for Computational Biomedicine (CCB)

Boston,Massachusetts

United States

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