Applications Due April 2, 2024
Review the information and application requirements on this page carefully before submitting.
We invite applications for the Center for Machine Learning and Health (CMLH) Fellowships in Digital Health Innovation. Each fellowship provides full support for one year for a Ph.D. student at Carnegie Mellon University who is pursuing cutting-edge research that advances digital health, broadly defined under one of the themes below.
For answers to common questions and more detailed policy information, check the fellowship Frequently Asked Questions (FAQ) page. For any remaining questions, contact cmlh@cs.cmu.edu.
The following three themes have been selected as criteria for the proposal submissions. Your application should identify which theme(s) your work falls under and argue why the project will advance the identified themes. Proposals without a strong connection to one of these themes will not be reviewed. However, you may interpret the themes broadly, and examples are included for each theme below.
The CMLH encourages applications from across the university developing creative technological solutions that advance one or more of the above themes. We welcome applications that involve diverse approaches and disciplines that apply to healthcare, including — but not limited to — machine learning, computer science, robotics, language technology, computational biology, electrical and computer engineering, biomedical engineering, chemistry, biological science, neuroscience, economics, psychology, sociology, public policy, business administration, law, human-computer interaction, and statistics.
Applicants must submit a three-page research proposal that describes the proposed work to be carried out during the fellowship. There are no specific format requirements and no template. Citations in a bibliography at the end are preferred. The three-page limit does not include the bibliography. Proposals that do not follow this format will not be considered.
Review of Proposals: The research proposal will be reviewed according to its fit within a theme, its innovation, feasibility and the overall quality of the project as measured by its contribution to fundamental research and potential broader impacts in digital healthcare. The evaluation committee will consist of faculty from CMLH and across CMU working in digital health and related areas from a broad spectrum of perspectives. The proposal should be written so the impact and plan are understandable to a researcher who is knowledgeable broadly about computation, machine learning and digital health, but who is not an expert in the chosen theme.
Final Selection: We expect to award several fellowships under this call.
Requirements of the fellowship: By accepting the CMLH Fellowship in Digital Health Innovation, you agree to the requirements stated below. Please contact the CMLH with any questions regarding the requirements before accepting the fellowship.
Please contact the CMLH via email with any questions at cmlh@cs.cmu.edu.