Research Associate - HSPH

Key Skills

Algorithms, Data science techniques, Environmental, Leadership Skill, Machine learning techniques, Statistics

Job Description

Overview

Located in Boston and the surrounding communities, Dana-Farber Cancer Institute brings together world renowned clinicians, innovative researchers and dedicated professionals, allies in the common mission of conquering cancer, HIV/AIDS and related diseases. Combining extremely talented people with the best technologies in a genuinely positive environment, we provide compassionate and comprehensive care to patients of all ages; we conduct research that advances treatment; we educate tomorrow's physician/researchers; we reach out to underserved members of our community; and we work with amazing partners, including other Harvard Medical School-affiliated hospitals.

The Department of Data Science at the Dana-Farber Cancer Institute (DFCI) seeks candidates with a strong background in statistics, machine learning, or computational biology to join a collaborative research team and provide quantitative analysis and computational support. The successful candidate will have a unique opportunity to lead study design and analysis components as part of multiple interdisciplinary research collaborations. There is room for growth in this position as the career ladder permits promotion to levels that lead groups of other quantitative scientists.

Responsibilities

The Department of Data Science at the Dana-Farber Cancer Institute offers an exceptional collaborative environment with experts in a wide range of areas including clinical trials, cancer genetics, immunology, epigenetics, machine learning, statistical software development, Bayesian methods, and alignment algorithms.

Qualifications

• Doctoral-level degree 
• Ordinarily have at least 2 years of postdoctoral experience 
• Evidence of potential for original or collaborative scholarship

Dana-Farber Cancer Institute is an equal opportunity employer and affirms the right of every qualified applicant to receive consideration for employment without regard to race, color, religion, sex, gender identity or expression, national origin, sexual orientation, genetic information, disability, age, ancestry, military service, protected veteran status, or other groups as protected by law.