Grants

The AHA Institute for Precision Cardiovascular Medicine is accepting applications from researchers for Data Grant Portfolio 4.0.

Applications are due July 31, 2019


GRAND CHALLENGE: Precision Health and Precision Medicine Grant

Conduct and explore modern experimental techniques (in all fields) coupled with robust data sources to make significant advances in understanding and/or deployment of precision health and precision medicine practices.

Data source examples include but are not limited to images, electronic health records, genetics and omic-related data, community engagement data (including social determinants of health), wearable devices, smartphone and other sensor related technology. Investigators at all career levels and across all disciplines are eligible to apply.

Maximum Funding Amount: $250,000 per year for 4 years, including 10% institutional costs ($1,000,000 cash total), with up to $50,000/year Amazon Web Services service credit for use on the AHA Precision Medicine Platform.


Artificial Intelligence and Machine Learning Grants

Build, test and refine artificial intelligence and machine learning algorithms using varying data sources, which may include, images, electronic health records, wearable devices, smart phones and other sensor-related technology, genetics, biology, and community engagement metrics.

Maximum Funding Amount: $200,000 over 2 years, and up to $50,000/year Amazon Web Services service credit for use on the AHA Precision Medicine Platform.


Artificial Intelligence and Machine Learning Training Grants

A training award for student researchers (undergraduate, graduate or pre- or post-doctoral) with at least a Bachelor’s degree and a mentor - to test and refine artificial intelligence and machine learning algorithms using varying data sources. Data sources may include: images, electronic health records, wearable devices, smart phones and other sensor-related technology, genetics, biology, and community engagement.

Maximum Funding Amount: $100,000 over 2 years, with up to $50,000/year Amazon Web Services service credit for use on the AHA Precision Medicine Platform.


Artificial Intelligence and Machine Learning Clinical Training Grant

A training award for student researchers (undergraduate, graduate or pre- or post-doctoral) with at least a Bachelor’s degree and a mentor - to test and refine artificial intelligence and machine learning algorithms using varying data healthcare system sources. Data sources may include: images, electronic health records, wearable devices, smart phones and other sensor-related technology, genetics, biology, and community engagement.

Maximum Funding Amount: $100,000 over 2 years, with up to $50,000/year Amazon Web Services service credit for use on the AHA Precision Medicine Platform.

How do we choose which applications to fund?

We’ll fund researchers from anywhere in the world who are working in the field of data science. We have grants that range from early-, mid-, and established career timelines. We also fund training grants for pre-doctoral as well as post-doctoral applicants.

We have funded researchers who have just started out and are working on their first project. And we’ve funded researchers who have had more than 20 projects previously funded.

You must meet the requirements of the individual grant to be considered by the Institute.


Frequently Asked Questions

Please Note: Human Subjects Research forms and Vertebrate Animal Subjects Research forms are not required at the time of application. If awarded, the grantee will be required to provide this information as part of the just-in-time information requested.

Meet our past grantees

Guido Falcone, MD, ScD, MPH

"Once we identify one of these [genetic] mutations, we can look at a combination of these mutations and try to gauge a person's risk even before that person has the disease. That's the world of precision medicine."

Stacey Knight, Ph.D.

“Our project takes those two very large datasets and uses the AHA Precision Medicine Platform to accelerate findings of cardiovascular disease-related genetic causes”

Bonnie Ky, M.D., M.S.C.E.

"Through the AHA’s Institute for Precision Cardiovascular Medicine, I’ve been fortunate to obtain funding for a project focusing specifically on using imaging to identify new patterns of cardiotoxicity in breast cancer patients.”

Anand Rohatgi, MD

"Using these large cohorts of people with available specimens and the deep phenotyping approach, we’ll better understand HDL’s precise function not just for the population as a whole but for specific individuals."