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Category: Research
Location: Worcester, MA
Shift: Day
Exempt/Non-Exempt: Exempt
Business Unit: UMass Chan Medical School
Department: School - Genomics and Computational Biology - W403700
Job Type: Full-Time
Salary Grade: 86
Union Code: Non Union Position-W63-Residents/Post Docs
Num. Openings: 1
Post Date: Jan. 31, 2025
The Weng Laboratory - Department of Genomics and Computational Biology
University of Massachusetts Chan Medical School The Weng Lab (https://www.umassmed.edu/zlab/) in the Department of Genomics and Computational Biology at the University of Massachusetts Chan Medical School invites applications for a postdoctoral research associate position.
The position's primary focus is applying computational approaches to study molecular mechanisms of gene regulation by integrating genomic, epigenomic, and transcriptomic data. The successful candidate will: conduct and publish high-quality research in peer-reviewed journals, contribute to research grant proposals to secure funding, and train and mentor new laboratory members, including supervising the work of junior graduate students.
Qualifications include a Ph.D. and/or M.D. in computational biology or a closely related field, a strong record of scientific productivity, and demonstrated excellence in computational biology research, particularly in gene regulation, transposon biology or related areas.
Applicants should submit a cover letter detailing qualifications and interest in the position, a current CV, and contact information for three professional references to Professor Weng: zhiping.weng@umassmed.edu
Applications will be reviewed on a rolling basis starting December 2024 and will remain open until the position is filled. Please contact Professor Weng (zhiping.weng@umassmed.edu) for additional information.
UMass Chan Medical School is an equal opportunity and affirmative action employer. We value diversity and inclusion, recognizing the critical importance of a diverse community in advancing innovation and excellence. We strongly encourage applications from individuals with varied experiences, perspectives, and backgrounds.
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