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Postdoctoral Fellow
Harvard University in Cambridge, Massachusetts
 
 
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Date Posted August 05, 2022
Category
Admin-Other Administrative Positions
Employment Type
Application Deadline Open until filled
 
 
 
 
 

Details


Title Postdoctoral Fellow
School Harvard T.H. Chan School of Public Health
Department/Area Department of Biostatistics/Quantitative Cancer Biology and Analysis
Position Description

We are seeking a candidate with expertise in computational and systems biology to work as part of a multidisciplinary team developing methods relevant to the study of genetics, gene regulatory networks, and the use of quantitative imaging data as biomarkers. Our goal is to use these methods to better understand the development, progression, and response to therapy. The successful applicant will work directly with Dr. John Quackenbush, but will be part of a community of researchers consisting of Dr. Quackenbush, Dr. Kimberly Glass, Dr. John Platig, and Dr. Camila Lopes-Ramos, and members of their research teams.

Basic Qualifications

A PhD in computational biology, biostatistics, applied mathematics, physics, biology, or related fields and demonstrated skill in methods and software development and the analysis of biological data are required.

Additional Qualifications

The ability to work as part of a large, integrated research team and strong verbal and written communication skills are essential. Previous work in cancer biology/cancer genomic data analysis is welcome but not required.

Special Instructions
Administrative questions regarding this position can be sent to Nicole Trotman at ntrotman@hsph.harvard.edu.
Scientific questions regarding this position can be sent to John Quackenbush at johnq@hsph.harvard.edu.
Contact Information
Nicole Trotman
Contact Email ntrotman@hsph.harvard.edu
Equal Opportunity Employer
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 2
Maximum Number of References Allowed 5
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