Fellowship Requirements

Center for Machine Learning and Health

The Center for Machine Learning and Health fellowship programs are designed to give Ph.D. students focusing on emerging technologies an opportunity to deepen their knowledge base and contribute meaningfully in making healthcare better. Healthcare is a vast sector — and our fellows' interests are just as broad as the technologies supporting the healthcare ecosystem. The requirements stated here apply to all CMLH Fellowships.

Requirements

General

  • Fellows must be a full-time Ph.D. student working on a project related to the theme of the fellowship at the time of the award for the duration of the fellowship.
  • The fellow is responsible for the requirements of the fellowship and must notify the CMLH if a change in status or project direction occurs.
  • Fellows must abide by and uphold the community standards of the university.
  • Fellows are expected to follow university intellectual property (IP) and research policies.
  • The student must be in good standing in their Ph.D. program for the duration of the fellowship.
  • Fellowships are nontransferable between students. If a fellowship recipient leaves the program prior to completing their 12-month term, any remaining fellowship funding is retained by the CMLH.

Promotion

  • Fellows provide a photo, brief biography and project abstract for the CMLH website and consent to use at the discretion of the CMLH for social media posts and other marketing purposes.
  • Recipients must allow sharing of the project title and project abstract with our sponsor, UPMC Enterprises, and other potential CMLH sponsors.
  • Provide a CV, project abstract and presentation slides to the CMLH to share with our sponsor, UPMC Enterprises, at the conclusion of the fellowship. (Project abstracts, progress reports and presentation slides should not include proprietary information.)

Publications

  • Fellows should acknowledge the CMLH in any of their publications related to the CMLH-funded work and notify the CMLH of any papers that result from the research. Example: "This work was partially supported by a fellowship from Carnegie Mellon University's Center for Machine Learning and Health to X.Y.," (where X.Y. are the fellow's initials). 

Support for the CMLH

  • Fellows will submit a progress report to the CMLH after six and 12 months of funding.
  • Students must present the research at a CMLH seminar series during or following the term of the fellowship. Fellows must present at a public event hosted by the CMLH. Invitees to the event will be at the discretion of the CMLH.
  • Fellows should endeavor to attend various CMLH seminars and social/virtual events.
  • Students who are awarded a CMLH fellowship and their faculty adviser(s) may be asked to review proposals in the future rounds of CMLH funding.

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