Amazon and the UCLA Department of Computational Medicine are engaging in a partnership in Machine Learning in Biomedical Sciences. Supported by a gift from Amazon, the collaboration will enable UCLA researchers to utilize large-scale computational resources to advance machine learning research in medically relevant applications.
We invite research proposals that leverage large-scale computing to develop and apply machine learning algorithms to medically relevant problems. Applicants should submit a one-page proposal that includes a project summary and a statement addressing how the project addresses each of the following three criteria, which will be used to evaluate applications:
- Solves a medically relevant problem – The proposal should describe the medically relevant problem the proposal addresses and what is the potential impact of the project on human health if it is successful. Any possibility of translation of the project into the UCLA Health System should be discussed.
- Innovative methodological machine learning research – The proposal should describe how the proposed research pushes the state-of-the-art in terms of research and applications of machine learning. The goal of the program is to support innovative methodological machine learning research. This includes developing new machine learning methods, novel extensions of existing methods and applying machine learning methods to medically relevant problems in innovative ways. Projects whose focus is limited to the application of machine learning software packages to biomedical data in standard ways are not considered responsive to this call for proposals.
- Leverages large-scale computing resources – The proposal should describe why the project requires the type of large-scale computing resources provided by Amazon Web Services (AWS) to be successful. A goal of the program is to leverage resources at AWS to enable computing at scale.
The proposal should also include a quarterly budget to be used for computing resources. Project budgets are to be capped at $50,000 of compute costs. If a project needs more computing, the project can apply for additional funding with an expedited review at a time when the project has come close to spending the $50,000.
In addition to the above, applicants should also submit a maximum one-page statement summarizing both the most machine learning related research they have done in the past 5-years and also the most medically relevant research they have done in the past 5-years. In addition, they should attach their most machine learning related publication and their most medically relevant publication during that period. Applications will also be evaluated on evidence that the applicant has previously conducted research that is medically relevant and involves innovative machine learning research.
Applications from teams of individuals are allowed, but a single primary contact should be designated. One-inch margins and 11 point or greater font should be used. A single pdf containing all the application material should be emailed to both Jason Ernst (email@example.com) and Sriram Sankararaman (firstname.lastname@example.org). Review and selection of applications will be done by a committee.
Deadline for submissions: December 14, 2018 at 5pm PDT
Anticipated start date: January 2019
Additional applications will be solicited at the end of Winter and Spring quarters in 2019