Research Fellow, Genomics & EHR Data Science

1200 The General Hospital Corporation; Boston (MA); On-site; USD 74,000 - 81,000; Full time

Job summary

The Urbut Lab at Mass General Brigham, affiliated with Harvard Medical School, seeks a highly qualified Research Fellow to develop dynamic Bayesian models using multimodal data and causal inference for EHR across cohorts and clinical trials.

This appointment at Massachusetts General Hospital offers collaboration across computational biology, biostatistics, and genetics, with on-site work at 185 Cambridge Street in Boston and access to world-class datasets and resources.

Qualifications

• The ideal candidate should have 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 skills in statistical analyses are highly preferred
• 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
• Familiarity with next-generation sequence data analysis tools strongly preferred
• Ability to adapt to rapidly changing and high-demand environments
• 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.

Skills

Computational biology

Bioinformatics

Statistical analyses

R

Python

AWS

Cloud computing

Independent work

Team collaboration

Academic publications

Education

Doctoral degree in computational biology, biomedical informatics, biostatistics, statistical genetics, genetic epidemiology, or computer science

Tools

Linux

Genomic analysis tools

Job description

The Urbut Lab at Mass General Brigham, affiliated with Harvard Medical School, seeks a highly qualified Research Fellow to develop dynamic Bayesian models using multimodal data and causal inference for EHR across cohorts and clinical trials.

This appointment at Massachusetts General Hospital offers collaboration across computational biology, biostatistics, and genetics, with on-site work at 185 Cambridge Street in Boston and access to world-class datasets and resources.