Global Mental Health Research Assistant - AI & Data

Harvard Medical School; Boston (MA); Hybrid; USD 55,000 - 70,000; Full time

Benefits offered by this job

Generous paid time off

Health insurance

Retirement plans

Job summary

Harvard Medical School’s Mental Health for All Lab seeks a Research Assistant to support global mental health studies OptimizeD and BRIDGE-AI. You will aid data analysis, literature reviews, manuscript preparation, and coordination with international collaborators.

The role blends public health, AI governance, and clinical research in a dynamic team. Ideal candidates have 2+ years of related experience, strong writing, and proficiency in Stata/R/REDCap.

Qualifications

• 2+ years related work experience or relevant coursework.
• Demonstrated interest in global mental health, digital mental health, or AI in healthcare.
• Strong writing and data management abilities.

Responsibilities

• Prepare manuscripts, abstracts, reports, and dissemination materials.
• Conduct literature reviews and evidence syntheses.
• Support data quality, follow-up assessments, and funder reporting.
• Coordinate study activities across teams and sites.
• Maintain IRB submissions and regulatory documents.
• Assist with data analyses in Stata, R, or related software.

Skills

Interpersonal skills

Communication

Organization skills

Quantitative methods

Qualitative methods

Stata

R

REDCap

Microsoft Office

Outlook

Zoom

Google Drive

AI governance

Education

Bachelor's degree in psychology/public health/social sciences

Master's degree in psychology/public health/social sciences

Tools

Stata

R

REDCap

Job description

Harvard Medical School’s Mental Health for All Lab seeks a Research Assistant to support global mental health studies OptimizeD and BRIDGE-AI. You will aid data analysis, literature reviews, manuscript preparation, and coordination with international collaborators.

The role blends public health, AI governance, and clinical research in a dynamic team. Ideal candidates have 2+ years of related experience, strong writing, and proficiency in Stata/R/REDCap.