Postdoctoral Fellow in Cancer Metabolism

Employer
MGH/CVRC
Location
Boston, Massachusetts (US)
Salary
NIH-level postdoctoral salary and full benefits
Posted
September 07 2019
Ref
SCIENCE
Position Type
Full Time
Organization Type
Academia
Job Type
Postdoc

A postdoctoral fellow position is available at the Massachusetts General Hospital and the Harvard Medical School.  The fellow will lead projects aimed to identify metabolic rearrangements in OXPHOS-competent or OXPHOS-incompetent cancer cells that may lead to potential treatments.  This research will incorporate a wide range of approaches using cutting-edge technologies and both cell and mouse models.  In addition, the fellow will interface with collaborators who are experts in diverse fields such as cancer metabolism and pharmacogenomics. 

Qualified candidates should have strong experimental expertise in biochemistry, molecular and cell biology. Proficiency in conducting mouse tumor studies is also required. S/he should possess excellent written and verbal communication skills, demonstrate critical thinking and independent problem-solving abilities, and have a strong publication record.  Prior research experiences in cancer metabolism and/or chemical biology are preferred. The search is primarily targeted towards scientists who are just finishing their PhD or have recently graduated.  We are looking for a dynamic and self-motivated individual that are able to take on a fast-paced, multidisciplinary project. 

To apply, please send (1) cover letter highlighting past research experience, your research interests and career goals, (2) CV and (3) the contact info of three references via email to Dr. Joanna Yeh at jyeh1@mgh.harvard.edu

Qualifications

Ph.D. degree in molecular & cellular biology, cancer biology, or chemical biology.

Desired Skills

Metabolic profiling

HPLC/Mass spectrometry

Metabolic flux analysis

Seahorse assays

Cell culture

Cell based assays

Cell imaging

Recombinant DNA techniques

Viral transduction

Flow cytometry

Enzymatic assays

Mouse tumor model and drug administration

Statistical analysis

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