Postdoctoral Fellow in Biomedical Informatics (Patel Lab)

Position Description

We invite applicants for a postdoctoral fellow position in Chirag Patel's group at Harvard Medical School in Boston, Massachusetts. The exposome is a promising and emerging modality to explain disease variation (papers in press in Nature Medicine) that impacts humans on all levels: from the single cell to populations, providing a rich substrate to do novel work. We welcome applications from recent PhD graduates with experience in developing approaches to analyze large multi-modal datasets and/or who wish to deploy the next generation of exposome AI models. These positions come with data ready to analyze: the candidate can focus on developing research findings and writing papers from day 1.

The successful candidate will work with Chirag Patel's group to produce highly impactful biomedical informatics research that presents new innovations in methods and novel findings that inform disease etiology. The candidate should be interested in focusing on multi-omic integration analytics, machine learning, and/or AI. In addition to carrying out research, the successful candidate will be expected to apply for fellowship funding, contribute to the writing of grants and manuscripts, participate in teaching and mentoring of lab members as needed, and otherwise contribute to overall lab operations and collaborative environment.

Salary and Benefits

This position is salaried and benefits eligible. Information regarding postdoctoral fellow salary, which is determined by the number of years post PhD, and benefits can be found at https://postdoc.hms.harvard.edu/guidelines.

With this appointment, you are represented by the Harvard Academic Workers (HAW) - UAW for purposes of collective bargaining and matters affecting your compensation and working conditions.

Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting discrimination on the basis of race, sex, ethnicity, color, national origin, religion, disability, or any other characteristic protected by law or identified in the university's non-discrimination policy.

Basic Qualifications

• Ph.D. or M.D./Ph.D. in areas such as Data Science, Statistics, Computer Science, Epidemiology, Environmental Health, or a related field. Demonstrated expertise in large scale analysis and familiarity with health-related datasets.

Additional Qualifications

• Advanced computational skills are required for the role in order to develop AI approaches to study the longitudinal physiology from diverse cohort populations.
• If visa sponsorship is needed, Harvard retains the discretion to determine which visa status is appropriate and whether a visa sponsorship application will ultimately be submitted, including payment of any applicable fees.