The 2025 call for proposals is open for CMLH Fellowships in Generative AI for Women's Health That Enables Self-Directed Patient Safety!

The Center for Machine Learning and Health (CMLH) is pleased to announce a 2025 call for fellowship proposals. 

We invite applications for the CMLH Fellowships in Generative AI for Women's Health That Enables Self-Directed Patient Safety. Each fellowship provides full support for one year for a Ph.D. student at Carnegie Mellon University who is pursuing cutting-edge research in this area.

Theme for Submissions: Generative AI for Women's Health That Enables Self-Directed Patient Safety

What Are We Looking For?

Research that leverages strengths in data-driven healthcare to encourage self-directed patient safety to achieve better health outcomes and better patient experiences. Self-directed patient safety includes topics such as health literacy, medication safety, adverse event reporting, communications advocacy and digital self-management. This work can empower patients and reduce harm in healthcare settings. 

Technologies that can support education and self-monitoring in women’s health with goals of early detection and timely intervention to reduce risk are valued. Women’s health includes areas such as pregnancy, menopause and perimenopause; reproductive health; osteoporosis; preventative care; etc.

Projects that can demonstrate the ability to foster partnerships with healthcare providers, improve communication, and support shared decision-making that lead to better health outcomes is important.

Fellowship Award Details

Each fellowship will provide support for one year for a CMU Ph.D. student whose research advances Generative AI for Women's Health That Enables Self-Directed Patient Safety. It provides:

• One year of tuition and stipend support (including summer stipend) for the student (nontransferable).
• $3,000 in funding to support the underlying research, including conference travel for paper presentation, equipment and human-subject experiments. 

This call includes a preliminary step with an Intent To Propose (ITP) submission. ITPs that are selected will advance to a full proposal submission. 

Important Dates

• Friday, October 31, 2025 — End of Day (midnight EDT): Intent to Propose (ITP) document due. No late submissions. CMLH will select relevant, high-impact projects from among these ITPs to submit a full proposal and provide a 15-minute presentation.
• Friday, November 14, 2025: Applicants selected to submit full proposals will be notified.
• Tuesday, December 2, 2025 — End of Day (midnight EST): Full applications due from invited applicants. Full applications will be accepted only from those invited based on their ITP submission. 
• Week of December 1–5: Applicants will be required to do a 15-minute presentation about their project. The presentation will be for the CMLH + other CMU community members invited by the CMLH (dates/times TBD)

Criteria and Eligibility

Who Is Eligible?

• Full-time, currently enrolled Ph.D. students at Carnegie Mellon University.
• Students with a primary research project related to Generative AI for Women's Health That Enables Self-Directed Patient Safety.

Criteria

• Students must be enrolled in the Ph.D. program for a full academic year for the duration of the fellowship.
• We welcome projects at any stage, both initial and mature. 
• No other fellowship should support the student throughout the duration of the award. The CMLH fellowship cannot be combined with any other fellowships. 

Intent to Propose Submission Instructions

All ITP submissions should follow the format described here. Submissions that do not follow the format will not be accepted. 

Submission Format

Submit one (1) single PDF file containing both of the following documents, in order:

1. Document One: ITP Proposal Document
2. Document Two: Student CV

All pages in the combined PDF (both ITP and CV) must be clearly marked "Confidential" in the header. The submission must not contain proprietary information.

Document One: ITP Proposal (PDF Format)

A single-page document (may be printed front and back), single-spaced, using 11-point font and divided into the following three sections:

• Section I: Student and Proposal Information
  • Student name, email, college/school and department.
  • Name of Ph.D. program currently enrolled in at CMU.
  • Faculty adviser(s).
  • Proposal title.

• Section II: Pitch Statement (One Sentence) 
  • Provide a one-sentence "elevator pitch" for your proposed project — a concise, engaging and persuasive statement that captures the essence of your idea and its excitement. The pitch should be memorable, compelling and succinct.
    
    
• Section III:The Research (½ Page, Maximum)
  • Provide an abstract describing your proposed project, its significance and potential impact. Explain why it represents a novel, innovative or unique approach to the problem. Your narrative should address the following questions, integrated smoothly within the half-page description:
    • Importance in Healthcare — Why is the problem important in healthcare? What challenge does your research aim to address?
    • Proposed Solution — What is your proposed solution? What new idea, technique, approach or method are you introducing? How does it align with the theme: "Generative AI for Women's Health That Enables Self-Directed Patient Safety?"
    • Impact — What is the expected benefit or impact of your innovation? How will it improve healthcare outcomes, efficiency or both?

Note: Bibliographies, images or charts should not be included in the ITP. If the ITP is selected to advance to a full proposal and presentation, additional information will be required.

Document Two: Curriculum Vitae (CV)

• Include your current CV (PDF format) after the ITP document.

Final Submission

• Combine Document One (ITP) and Document Two (CV) into a single PDF file.
• Label all pages with "Confidential" in the header.
• Submit the complete file via email attachment to cmlh@cs.cmu.edu. 

Contact the CMLH via email with any questions: cmlh@cs.cmu.edu.

Visit our Frequently Asked Questions for more information about the fellowships! 

Contact the CMLH with any questions.