Research Assistant III Non-Lab

The Mental Health for All Lab promotes the generation of knowledge and its effective utilization with the goal of contributing to the reduction of the global burden of mental health problems through task-sharing scale-up and digital interventions. The research program is based in the Department of Global Health and Social Medicine at Harvard Medical School and is under the direction of Prof. Vikram Patel and is co-led by Dr. John Naslund.
The Mental Health for All Lab is seeking a Research Assistant (RA) to support two major global mental health research programs: OptimizeD, a large precision medicine trial for depression in India funded by the National Institute of Mental Health (NIMH), and BRIDGE-AI, a Wellcome-funded study focused on the safe and equitable integration of artificial intelligence into clinical supervision for task-shared mental health care. The OptimizeD study aims to optimize treatment for depression by determining which patients will do better on antidepressant medication versus behavioral activation psychotherapy through a machine learning-generated precision treatment rule. More information about the study can be found in the study protocol: https://link.springer.com/article/10.1186/s12888-025-07030-9?utm_source=rct_congratemailt&utm_medium=email&utm_campaign=oa_20250730&utm_content=10.1186%2Fs12888-025-07030-9
BRIDGE-AI will adapt and evaluate an AI tool to improve therapy quality in India and develop an ethical and governance framework for the safe, equitable, and responsible use of AI in mental health supervision. The project combines global mental health, implementation science, artificial intelligence, bioethics, and lived-experience perspectives.
This position is intended for an early-career researcher interested in gaining hands-on experience at the intersection of global mental health, clinical research, data science, and responsible AI. During the initial phase of the appointment, the RA is expected to divide their effort between OptimizeD and BRIDGE-AI. As OptimizeD activities are completed, the position will transition primarily to BRIDGE-AI.
Contribute to the preparation of scientific manuscripts, abstracts, reports, presentations, and dissemination materials for both studies.
Conduct literature reviews and evidence syntheses to support analyses, manuscripts, and study activities.
Support the completion and close-out of Optimize-D, including monitoring outstanding follow-up assessments, data quality, study documentation, and funder requirements.
Support BRIDGE-AI implementation, including study coordination, data analysis, AI evaluation activities, and liaison with technical and clinical collaborators.
Support BRIDGE-AI ethics and governance work, including stakeholder workshops and focus groups, synthesis of findings, and development of guidance for the responsible use of AI in clinical supervision.
Prepare and maintain IRB submissions, amendments, regulatory documentation, and study files.
Coordinate meetings and communication with collaborators, funders, governance bodies, and international partners.
Assist with the organization, management, and documentation of quantitative and qualitative datasets and support analyses in Stata, R, or related software.
Support NIMH and Welcome Trust reporting, data submissions, and other project deliverables.
Undertake other research and project coordination activities as needed.
As part of your application, we recommend including a writing sample that will help us better understand your qualifications and background. This can provide valuable insight into your experience and interest in the role.
Basic Qualifications:
College background in a related field of research study.
2 or more years of related work experience (relevant coursework may count towards experience).
Additional Qualifications and Skills:
Bachelor's or Master's degree in psychology, public health, social sciences, or related field.
Excellent interpersonal and communication skills.
Demonstrated interest in global mental health, digital mental health, artificial intelligence in healthcare, or related areas.
Strong organization skills with keen attention to detail, able to prioritize, use discretion with sensitive or confidential information, and manage multiple assignments simultaneously.
Experience with quantitative and qualitative research methods.
Strong written communication skills, as evidenced by prior academic publications and/or presentations.
Competency in a variety of applications such as Stata, R, Microsoft Office, Outlook, REDCap, Zoom, Google Drive/OneDrive, as well as familiarity with AI-enabled research tools for tasks such as literature reviews, evidence synthesis, and research support. Confidence to adapt/learn if not familiar with an application.
Familiarity with issues related to research ethics, data privacy, AI governance, or responsible AI is desirable.
Ability to work collaboratively with individuals from diverse backgrounds.
Ability to adapt and remain flexible in a changing environment.

Employment type
Full-time

Work arrangement
Hybrid