AWS Machine Learning Research Awards

Funding academic research at the forefront of machine learning

The AWS Machine Learning Research Awards (MLRA) assists faculty, PhD candidates, and graduate students with research to advance the frontiers of machine learning (ML) and its application across a wide range of problems---from finding new therapies for cancer to solving climate change and exploring outer space. MLRA provides eligible researchers and university programs cash awards and AWS Promotional Credits so that they can do more faster using the most advanced compute, analytics, and machine learning tools available in the cloud.

Machine learning is still in its evolutionary stage with much of the progress coming from research on innovative algorithms, better data collection and preparation methods, and newer techniques such as reinforcement learning. Until recently, lack of access to the latest compute, storage, and networking has been a blocker for ML research. MLRA solves this problem by offering unrestricted cash awards and access to cutting-edge infrastructure and managed services through AWS Promotional Credits for selected applicants. MLRA also offers award recipients opportunities to participate in AWS events and receive live one-on-one training sessions with AWS data scientists and engineers.

To get started, submit your application here.

Program features

Funding

Awards are distributed at the department and project level and are structured as one-time unrestricted gifts to academic institutions.

AWS Promotional Credits

Awards include AWS Promotional Credits that are redeemed towards eligible AWS Services.

Training

We provide recipients with training resources, including tutorials on how to run machine learning on AWS and hands-on sessions with Amazon scientists and engineers.

Research Seminar

Award recipients are invited to a research seminar where they can discuss the progress of their work and interact with other award recipients and Amazon scientists.

Success stories

Featured story

Detecting and starting treatment of autism spectrum disorder (ASD) at an age of 18 to 24 months can increase a child’s IQ by up to 17 points—in some cases moving them into the “average” child IQ range of 90-110 (or above it)—and improving the child's quality of life significantly. Researchers at Duke University are using Machine Learning on AWS to create a faster, less expensive, more reliable, and more accessible system to screen children early for ASD.

See all success stories »

Researchers Are Using Machine Learning to Screen for Autism in Children (3:16)

Apply

In order to apply applicants should contact us at the below email address and request an application. Please note that as part of your application you must include your name, association with a university, a proposal summary detailing how your work will contribute or advance ML research, and requested award amount. Applicants submitted by or on behalf of a university, faculty, or a university department may be required to complete a conflicts check and certification of eligibility as part of their application in order to receive the award. Incomplete applications may not be considered.