Postdoctoral Research Fellow - Institute for Aging Research, Albert Einstein College of Medicine
Postdoctoral Research Fellow
Institute for Aging Research
Albert Einstein College of Medicine
A multidisciplinary group of researchers that aims to understanding the biological mechanisms of healthy aging in human cohorts enriched for longevity is seeking postdoctoral fellows to join their team at Einstein's Institute for Aging Research, a leading institution in human aging research, headed by Nir Barzilai, M.D. We offer a stimulating and collaborative environment for candidates with an interest in the biology of aging and omics. Recent NIH-funded projects include discovery of resilience mechanisms to Alzheimer's disease and genomic regulation of pathways implicated in longevity. Drs. Nir Barzilai, Sofiya Milman, and Zhengdong Zhang are looking for innovative, motivated candidates, who can work independently but also collaborate closely with clinical, basic and computational researchers. Applicants will be expected to apply and develop computational tools to model and address questions in human biology and aging. T32 funding is available and transition to a faculty position is possible. Additional information about the Institute can be found at www.superagers.com.
Candidates should have a Ph.D. or equivalent degree in computational biology or statistical genetics. Proficiency in a programming language (e.g. R, Matlab or Python) and knowledge of computational genetics are required. Experience with machine learning is desirable. Proficiency with analyzing large data sets is preferred.
Compensation: This position is remunerated according to NIH guidelines and comes with a generous package of University benefits.
As soon as possible
How to Apply:
Please send a CV and cover letter to Dr. Nir Barzilai at firstname.lastname@example.org or Dr. Sofiya Milman at email@example.com.
The Albert Einstein College of Medicine is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.