Position Summary:
We are searching for a creative, independent, and collaborative person to work within the Computational Analysis of Biomarkers Program of Einstein College of Medicine’s newly established Integrated Imaging Program for Cancer Research (IIP-CR) in New York City (www.bit.ly/3Xrg7Y6). The IIP-CR is a new initiative to investigate the hypothesis that a common mechanism regulating cancer metastasis can be targeted in breast, pancreas, and lung carcinomas. The candidate will be the local resident expert in the design, development, and utilization of advanced image analysis techniques to aid a multidisciplinary team of cancer biologists and physician scientists in analyzing patient and mouse data in multiple forms, including Multiplexed IHC and IF, spatial genomics, and intravital imaging. Techniques will include quantitative digital pathology, artificial intelligence, and machine learning. This position is an opportunity for a motivated individual to make a direct and significant impact upon patient care by working directly with physician-scientists on retrospective and prospective clinical trials.
Minimum Education and Experience:
Applicants must have an M.Sc. or Ph.D. in a relevant field (e.g. (bio)informatics, cancer biology, biomedical engineering, applied mathematics, etc.) and have experience in image analysis, artificial intelligence, and machine learning programming. Experience in genomic analysis or biomarker development is a plus. The ability to communicate techniques and algorithms to non-experts is crucial.
Special Instructions:
To apply, applicants must submit: 1) A cover letter describing the applicant’s interest in the position, 2) A curriculum vitae, and 3) Names of three referees that we may contact for letters of reference. Email applications with the subject “CAB Application” to David Entenberg (david.entenberg@einsteinmed.edu).
Salary range: $65,000 - $100,000 depending on position and experience at time of arrival.
Employer Name: Albert Einstein College of Medicine. Einstein is an equal opportunity employer.