Research Fellow

Mass General Brigham • Boston, MA

3d • Onsite

About The Position

The laboratory of Dr. Sarah Urbut, located within Mass General Brigham’s Heart and Vascular Institute’s (MGB HVI) Cardiovascular Research Center (CVRC) and affiliated with the Broad Institute of Harvard & MIT and Harvard Medical School, is seeking a highly qualified applicant for a Research Fellow position. This role focuses on dynamic modeling using multimodal data and causal inference for Bayesian analysis of EHR across cohorts, hospital-based biobanks, and clinical trials. The successful candidate will be appointed as a Research Fellow at Massachusetts General Hospital and Harvard Medical School, leveraging resources from world-class institutions. The research involves integrating electronic health records (EHR) with genetics for prediction and discovery, utilizing various genetic datasets (genome-wide arrays, whole exome sequencing, whole genome sequencing) and multi-omics data. The candidate will join an interdisciplinary team and contribute to innovative research studies aimed at guiding future therapeutic development and diagnostic tools for cardiovascular disease. The position offers a unique opportunity to engage in cutting-edge science and contribute centrally to biomedical research within vibrant research environments.

Requirements

• Received (or expect to receive soon) a doctoral degree. A doctoral degree will be required to complete onboarding.
• First (or co-first) author of one or more peer-reviewed scientific publications
• Excellent English verbal and written communication skills
• Able to work both independently and in a team
• Doctoral degree in computational biology, biomedical informatics, biostatistics, statistical genetics, genetic epidemiology, or computer science.
• Strong record of productivity, motivation, adaptability, and collaboration.
• Exceptional oral and written communication skills.
• Strong background in computational biology and bioinformatics.
• Strong demonstrable proficiency in Linus, R, python and AWS use.
• Strong facility with cloud computing.
• Prior experience in human genetic analyses and bioinformatics analyses of publicly available datasets.
• Ability to adapt to rapidly changing and high-demand environments.

Nice To Haves

• Strong skills in statistical analyses are highly preferred.
• Familiarity with next-generation sequence data analysis tools strongly preferred.
• Knowledge of cardiovascular disease is not required.

Responsibilities

• Construction and implementation of cloud-based pipelines for genomic, polygenic risk scoring, and biostatistical analyses.
• Processing and quality control of next-generation sequence data.
• Processing and quality control of multi-omics data.
• Statistical analyses of genotype-phenotype association analyses, with summarization and graphical representations.
• Organizing, manipulating, and harmonizing new datasets across different formats and robust synchronization with existing datasets and databases.
• Phenotypic derivation from electronic health record structured and unstructured data.
• Construction, implementation, and sensitivity analyses of biostatistical models in classical epidemiology, genetic epidemiology, and machine learning.
• Lead and contribute to manuscript preparation as well as internal and external project-team reports.
• Actively participate and present in project meetings.

Benefits

• Consideration for employment without regard to race, color, religious creed, national origin, sex, age, gender identity, disability, sexual orientation, military service, genetic information, and/or other status protected under law.
• Reasonable accommodation for individuals with a disability to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree