Mass General Brigham - Boston, MA

posted 4 months ago

Part-time - Intern
Remote - Boston, MA
Ambulatory Health Care Services

About the position

The Research Analyst Intern will participate in clinical and genetic epidemiology research focusing on cardiovascular, kidney, and metabolic conditions within the Brigham and Women's Hospital Department of Pharmacy Services. This research is supported by the National Heart, Lung, and Blood Institute, the American Society of Nephrology, and the BWH Khoury Innovation Fund. Under the supervision of the Principal Investigator and research staff, the Research Analyst Intern will conduct analyses and develop pipelines for various types of omic data as well as clinical datasets from epidemiologic studies and clinical trials. The primary responsibilities of this position include curating and maintaining large clinical and molecular datasets for downstream analysis, developing and maintaining pipelines for accessing and analyzing data, and supporting clinician-researcher access to these datasets. The intern will also participate in the analysis of these datasets, gaining experience with the management of cardiovascular disease and the conduct of clinical research. This includes potential areas such as human subjects research protections, epidemiology, biostatistics, and other areas relevant to the candidate's background and career goals depending upon the current stage of each research study. Career development through mentoring and seminars will be an important component of this position for students with an interest in pursuing a career in epidemiologic research. The Research Analyst Intern will have the opportunity to work with the hospital's high-performance computing cluster, other cloud-based platforms for biomedical research, and a rich array of clinical and molecular data. This position is designed to provide a comprehensive learning experience in the field of epidemiology and clinical research, allowing the intern to develop essential skills and knowledge that will be beneficial for their future career.

Responsibilities

  • Curating and maintaining large clinical and molecular datasets for downstream analysis
  • Developing and maintaining pipelines for accessing and analyzing data
  • Supporting clinician-researcher access to these datasets
  • Participating in the analysis of these datasets
  • Processing and manipulating an array of clinical and molecular data types
  • Developing, enhancing, and maintaining clinical and molecular databases
  • Creating publication-ready visualizations, tables, and other data summaries
  • Providing computational and statistical programming support to researchers
  • Contributing to writing abstracts and manuscripts
  • Triage issues to the Principal Investigator and other staff as appropriate
  • Assisting with the development of study procedural documents
  • Other relevant duties, as assigned.

Requirements

  • Bachelor's degree required, plus must be a current graduate student in bioinformatics, computational biology, or another relevant field in good standing
  • Strong programming skills and experience in R/RStudio (especially tidyverse packages), Python, shell scripting, and Apache Spark/SQL
  • Previous experience with high-performance Linux computing cluster (lsf system) and cloud-based computing
  • Experience with multiple regression, multiple testing considerations, survival analysis, meta-analysis, and instrumental variable (Mendelian randomization) analysis
  • Previous experience with biomedical data, including clinical and molecular data (genomics, proteomics, etc.) preferred
  • Experience with population and statistical genetics, such as population stratification, fine mapping, etc. is preferred
  • Must obtain human subjects research certifications per hospital policy

Nice-to-haves

  • Experience with population and statistical genetics, such as population stratification, fine mapping, etc.

Benefits

  • Career development through mentoring and seminars
  • Opportunity to work with high-performance computing cluster and cloud-based platforms for biomedical research
  • Experience with a rich array of clinical and molecular data
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