Sheryl and Dan Tishman Postdoctoral Fellowship

 

 

Mission 

To recognize and support exceptional candidates applying for postdoctoral positions at the Dominick P. Purpura Neuroscience Department with experience regarding cellular, molecular, systems, behavioral, cognitive, developmental, computational and/or clinical neuroscience research at Einstein. 

 

Vision

We believe that postdoctoral fellows are major contributors towards the excellence of our research program and future leaders in Neuroscience. 

 

Award

The fellowship will provide a supplement of $20,000 per year, above and beyond the NIH salary guidelines. The initial award will be for a period of three years, which may be extended upon extending a postdoctoral fellowship, or securing a first author publication during the initial award period.

 

Eligibility Criteria

1. Outstanding postdoctoral candidates with a solid publication track, that are interested in an eligible Neuroscience laboratory at Einstein are welcome to apply. 

2. Non-US applicants are eligible. 

3. The applicant and proposed project must be sponsored by a Dominick P. Purpura Department of Neuroscience investigator.

 

Application Instructions

1. Applicants should submit a CV, two reference letters, a (1-2 page) project summary and a letter of support from an Einstein postdoctoral mentor to neuroscidept@mail.einstein.yu.edu with the subject "Tishman Fellowship." 

2. Applications are considered on a rolling basis. 

3. Any questions or concerns about the program should be forwarded to the aforementioned email address. 

 

Albert Einstein College of Medicine, Inc. is an equal opportunity employer committed to hiring minorities, women, individuals with disabilities and protected veterans. Einstein’s mission is rooted in its history of an enduring commitment to diversity and the enhancement of human health in the spirit of social justice. Inspired by Albert Einstein, the College of Medicine strives to create a diverse faculty and student body without gender, racial and ethnic bias.