Fellowship in Digital Health and AI for Health at Johns Hopkins Bloomberg School of Public Health 2026
- Omran Aburayya
- 3 days ago
- 3 min read
If you’re a Bloomberg School of Public Health (BSPH) student driven by a passion for digital health and artificial intelligence in global health systems, the Fellowship in Digital Health and AI for Health is an open door to deepen your expertise and make an impact. Here's everything you need to know about this exciting opportunity.
🎓 Fellowship Summary
Location: Johns Hopkins University, Center for Global Digital Health Innovation, Baltimore, Maryland (with some remote options noted as global)
Level: Open to current BSPH (Master’s-level) students
Target Group: BSPH students interested in digital health, AI applications, global health research
Fields of Focus: Digital health, artificial intelligence, global health innovation, evidence synthesis, primary research
Value & Coverage: Financial support of up to US$1,000 per student, depending on the project and number of applicants
Duration: Approximately 8 months
Application Deadline: Friday, September 12, 2025 (this is exact; do not rely on relative terms)
Start Date: Likely September/October 2025 (shortly after application deadline; exact start date not specified)
Eligible To: Current BSPH students with interest in digital health and AI research
📚 Scholarship Overview
The Fellowship in Digital Health and AI for Health is designed to nurture applied scholarly innovation in global digital health:
Fellows are matched with faculty mentors and work closely over eight months to contribute to ongoing research projects. They can engage in evidence synthesis (such as systematic or scoping reviews) or primary research with defined outputs. Deliverables may serve as part of practicum or capstone requirements .
The program aims to equip fellows to bridge academic knowledge with concrete research outputs that strengthen global digital health evidence and equity .
🧩 Fellowship Structure, Curriculum & Activities
Number of Fellowships: 14 total slots .
Funding: Up to US$1,000 per fellow, based on project relevance and application volume .
Mentorship: Fellows are paired with faculty mentors aligned with their interests .
Duration: Approximately 8 months .
Outputs: Fellows will deliver a defined research product, chosen in coordination with mentors, among options such as systematic/scoping reviews, policy or evidence briefs, primary-data–based research reports, or other agreed-upon deliverables .
🎁 Fellowship Benefits
Financial Support: Up to US$1,000 each to alleviate costs and support participation .
High-Quality Mentorship: One-on-one pairing with faculty experts in AI, digital health, global health research.
Meaningful Research Outputs: Your work can feed into capstone or practicum projects and contribute to global health evidence.
Professional Development: Engage directly in digital health innovation, enhancing your research skills and real-world policy relevance.
✅ Eligibility Criteria
Current enrollment as a student at the Johns Hopkins Bloomberg School of Public Health (BSPH).
Demonstrated interest in digital health, AI for health, and global health issues.
Ability to propose a focused research topic and approach (see application process below).
Academic rigor and original thinking—while AI tools may help structure ideas, the intellectual work must be your own .
📝 Application Procedure
Submit the following by September 12, 2025:
Curriculum Vitae (CV).
Two-page proposal selecting one of the priority topics. Your proposal must include:
A clear understanding of the topic and personal motivation.
Key issues, gaps, or challenges within that area.
Proposed methods and potential outputs.
Submission format: via the official Google Form
Contact for questions: Casey Sheils, csheils3@jh.edu (use exact email) .
Original thinking is strongly encouraged; LLMs may assist but must not replace your intellectual work .
🧭 Priority Topics
AI-based tools for automating data analyses (e.g., mortality, early warnings; collab with Vital Strategies; D4H project) – Supervisors: Madhu Jalan & Katya Saksena – Slots: 2 .
Chatbots for infoveillance (literature synthesis, stakeholder engagement) – Supervisors: Rose Weeks & Smisha Agarwal – Slots: 2 .
Research agenda for Mobile Phone Surveys for RMNCAH&N – Supervisor: Melinda Munos – Slots: 1 .
Evaluating AI-assisted ambient scribing model – Supervisors: Smisha Agarwal & Suruchi Gupta – Slots: 2 .
AI-enabled approaches to improve survey data quality (e.g., anomaly detection, guidelines, prototypes) – Supervisor: Shivam Gupta – Slots: 1 .
Literature review: Digital health & AI in humanitarian emergencies (deliverable: presentation for Global Digital Health Forum in December) – Supervisors: William Weiss & Aral Surmeli – Slots: 1 .
Project TRACE: Data pipeline to detect structural health inequities (spatial analysis, dashboard) – Supervisor: Adler Archer – Slots: 3 .
Cost-effectiveness of Vector-Cam (AI vector surveillance tool) – Supervisor: Sunny Patel – Slots: 2 .
