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Computational Research Assistant- CHIP

Job in Boston, Suffolk County, Massachusetts, 02298, USA
Listing for: Boston Children’s Hospital
Full Time position
Listed on 2026-02-16
Job specializations:
  • Research/Development
    Data Scientist, Clinical Research, Research Assistant/Associate
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below

Overview

The Computational Health Informatics Program (www.

CHIP.org) at the nation’s top pediatric institution, Boston Children’s Hospital, a Harvard Medical School affiliate, is seeking a Computational Research Assistant to support a research project focused on evaluating how clinicians interpret continuous glucose monitoring (CGM) data and how these interpretations compare to outputs generated by large language models (LLMs). The project aims to establish a benchmark of "gold-standard" CGM interpretations to inform safe, effective AI tools for diabetes care.

The Research Assistant will play a central role in coordinating clinician responses, managing study data, and conducting basic quantitative and qualitative analyses comparing clinician responses to AI outputs.

This position is ideal for someone interested in clinical research, health data analysis, or digital health applications, and who wants hands-on experience working at the intersection of clinical medicine and AI. Prior background in AI is not required.

Key Responsibilities
  • Coordinate the collection of clinician-authored CGM interpretations.
  • Preparation of summaries, scheduling, tracking responses, and communication.
  • Perform basic data analysis of clinician responses and model outputs, including descriptive statistics and structured comparisons.
  • Support preparation of figures, tables, and materials for co-authored manuscripts and presentations.
Minimum Qualifications

Education:

  • Bachelor's Degree in STEM

Experience:

  • Comfort working with structured datasets (e.g., spreadsheets, CSV files).
  • Basic experience with data analysis tools (e.g., Excel, R or Python).
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