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美国丹娜法伯癌症研究院2025年招聘博士后(数据科学方向)

时间:2025-02-05 12:08:27  公招网(www.gongzhao.com)
  博士后招聘

美国丹娜法伯癌症研究院2025年招聘博士后(数据科学方向)

Postdoctoral Fellowships - Department of Data Science

Dana-Farber Cancer Institute

Location: Boston, MA

Job Number: 7294710 (Ref #: df41777)

Job Description

Located in Boston and the surrounding communities, Dana-Farber Cancer Institute is a leader in life changing breakthroughs in cancer research and patient care. We are united in our mission of conquering cancer, HIV/AIDS and related diseases. We strive to create an inclusive, diverse, and equitable environment where we provide compassionate and comprehensive care to patients of all backgrounds, and design programs to promote public health particularly among high-risk and underserved populations. We conduct groundbreaking research that advances treatment, we educate tomorrow's physician/researchers, and we work with amazing partners, including other Harvard Medical School-affiliated hospitals.

The Department of Data Science at Dana-Farber Cancer Institute welcomes recent Ph.D. graduates and doctoral candidates nearing graduation who have research interests in applied statistics, machine learning, or computational biology to apply for our postdoctoral fellows program. This program offers the flexibility to join a research group in our department, be co-mentored by two or more faculty members, and/or work collaboratively as a data scientist with DFCI investigators outside our department. Our department has a diverse group of faculty members that can serve as mentors and DFCI has numerous world renowned basic biologists and clinical investigators looking for collaborators with your skills.

Please visit our website https://ds.dfci.harvard.edu/postdocs to view the list of mentors and submit application.

We are having a virtual Informational Session on November 6,2024 from 1pm-2pm EST. Please submit an application to rsvp.

Recent Ph.D. graduates and doctoral candidates nearing graduation who have research interests in applied statistics, machine learning, or computational biology are encouraged to apply.

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