August 15, 2024
National Heart, Lung, and Blood Institute (NHLBI)
The purpose of this Notice is to inform the research community of the release of a program solicitation on August 9, 2024, announcing the availability of a fellowship program focused on training in the application of novel and innovative artificial intelligence (AI) and machine learning (MI) approaches to data-driven research problems. The full program solicitation is available on the TOPMed Administrative Coordinating Center (ACC) website: (https://topmed.nhlbi.nih.gov/2024-topmed-fellowship).
The TOPMed program has generated a collection of genomic, epigenomic, transcriptomic, proteomic, and metabolomic data (see details at https://topmed.nhlbi.nih.gov/) from over 200,000 well-phenotyped individuals to enable detailed characterization of these study participants. This data is available for access by researchers in the BioDataCatalyst and dbGaP databases. Together, this multi-omics data coupled with clinical, imaging, EHR, and environmental data, present both unprecedented opportunities for data-driven discovery and challenges. Analyzing and combining these datasets are currently limited by both practical and conceptual constraints. With this fellowship program, TOPMed seeks to enable and accelerate AI/ML-driven mining of these rich datasets from diverse populations.
The goal of the TOPMed Fellowship program is to promote broad participation and engagement of early-career researchers in applying AI/ML approaches to address challenging research questions in areas of HLBS, including Womens Health Research and bias in AI/ML algorithms or data. The program will provide support for researchers who will leverage the trans-omics resources of TOPMed and beyond to gain access to training, data, and analytical tools needed to rapidly develop research skills required in the AI/ML field. The fellowship opportunities are aimed to facilitate the career advancement and/or transition of scientists to the next steps in their scientific careers and to develop a cadre of diverse scientists capable of applying AI/ML in health research.
Applications must focus on an area within NHLBIs mission and propose to use existing or up-coming data to conduct discovery research. In addition, the solicitation encourages submission of proposals that use an AI/ML method as one of the main analytic tools in the research plan or include an AI/ML training plan beyond the main research plan. The use of TOPMed data as either the primary or secondary dataset is strongly encouraged.
Individuals from underrepresented racial and ethnic groups as well as individuals with disabilities are always encouraged to apply for NIH support (see NOT-OD-20-031).
Please see https://topmed.nhlbi.nih.gov/2024-topmed-fellowship for specific information regarding application budget and number of awards. The application due date is October 29, 2024, 5:00 pm Eastern Daylight Time (EDT).
A technical assistance webinar will be held on September 5, 2024, 3:00 pm EDT. Dial-in information for the call is posted on the ACC website and slides will be made available on the website after the webinar.
Please direct all inquiries regarding this Notice to:
Application Submission Contact
TOPMed Administrative Coordinating Center (ACC)
Website: https://topmed.nhlbi.nih.gov/2024-topmed-fellowship
Program Contacts
Jane Ye, Ph.D.
Division of Lung Diseases
National Heart, Lung, and Blood Institute (NHLBI)
Telephone:301-480-7447
Email: [email protected]
Huiqing Li, Ph.D.
Division of Cardiovascular Sciences
National Heart, Lung, and Blood Institute (NHLBI)
Telephone: 301-435-0554
Email: [email protected]
IIana Goldberg, Ph.D.
Division of Blood Diseases and Resources
National Heart, Lung, and Blood Institute (NHLBI)
Telephone: 301-496-8587
Email: [email protected]