AIM-AHEAD Research Fellowship

About AIM-AHEAD

The AIM-AHEAD coordinating center was established to enhance diversity in the field of artificial intelligence and machine learning (AI/ML), with emphasis on reducing health disparities and promoting health equity. We hope to achieve this by engaging in a fair, equitable, and transparent process of building a consortium of AI/ML to promote health equity and an inclusive and diverse workforce. Many communities have untapped potential to contribute new expertise, data, recruitment strategies, and cutting-edge science to the AI/ML field. AIM-AHEAD Coordinating Center seeks to increase participation and engagement through mutually beneficial partnerships, stakeholder engagement, and outreach to advance health equity.

 

 

Fellowship Information

The AIM-AHEAD Research Fellows Program will engage a group of early-career researchers from under-represented populations to actively participate in biomedical research that involves the use of AI/ML methodologies on Electronic Health Record Data, Clinical cohort and genomic data across various populations.

 

The program is open to individuals conducting research at the intersection of healthcare practice and delivery, AI/ML methods, and the advancement of health equity. The AIM-AHEAD Consortium seeks projects that represent diversity across fields of study, institutions, geography, and investigators.

 

This Fellowship is supporting early-career researchers (graduate students, postdocs, junior faculty, and others conducting research outside of an academic institution, within 10 years of graduation) in implementations of novel and innovative data science and data-focused research problems. The program will provide both funding support and additional AIM-AHEAD resources, giving priority to researchers from under-represented populations who will leverage AIM-AHEAD to gain access to training, data, and infrastructure needed to rapidly develop research skills required in the AI/ML field. The research project needs to focus on AIM-AHEAD North Star (III): Use AI/ML to address disparities and minority health in behavioral health, cardiometabolic health, and cancer.

 

More information about the Fellows of the AIM-AHEAD Research Fellowship cohort #1, including their profiles and research projects.

 

AIM-AHEAD Research Fellows cohort 2 began on September 15th, 2023.

 

Dataset options (more information available on below datasets/cohorts):

Dataset Brief Description Data Allowed Size Analysis Platform Tools
A customized subset from OCHIN Community Health Equity Database EHR data from Underserved communities HIPAA Limited dataset, individual-patient level data with dates and zipcodes if needed for research A customized subset will be created for the research question of awarded fellow from over 6 million records AIM-AHEAD Service Workbench
Curated AIM-AHEAD Data Bridge (AADB) Library OR custom curated dataset from MedStar Health EHR Curated dataset options of EHR data from underserved communities De-identified dataset; Multiple curated dataset options (see detailed information below for dataset descriptions) Varies from dataset to dataset; MedStar EHR includes population of 4+ million records AIM-AHEAD Data Bridge
60+ studies from NHLBI BioData Catalyst Selected large-scale cohorts related to heart, lung, blood and sleep disorders. Includes both prospective clinical studies and associated genomic TOPMED data. De-identified dataset. Including individual level genomic (TOPMED full genomes) and clinical datasets. Additional description

List of studies : 60+ studies are available to choose from
NHLBI BioData Catalyst PIC-SURE and Seven Bridges Platforms

Selected Open datasets on AWS

A variety of datasets available including clinical and genomic data

Public data, and controlled access data (depends on dataset)

Selected Open datasets on AWS

AIM-AHEAD Service Workbench

NIH All of Us

The All of Us Research Program is building one of the largest biomedical data resources of its kind.

The All of Us Research Hub stores health data from a diverse group of participants from across the United States.

Additional descriptions

616,000+ Participants

360,000+ Electronic Health Records

444,000+ Biosamples Received

All of Us Researcher Workbench

AIM-AHEAD Service Workbench - Infrastructure available for working with 1) OCHIN and 2) AWS Open Datasets. More information is available here.

AIM-AHEAD Research Fellowship OCHIN Data Dictionary

Read the Call for Proposal for Research Fellowship Cohort 2 

Application Process:

Step 1: Click here to register as a “mentee/learner” on AIM-AHEAD Connect (our Community Building Platform)

Step 2: Click here to submit a fellowship application for review using InfoReady platform*.

 * To submit your application in InfoReady, please use Chrome, Firefox, or Edge. If you're using Safari, make sure to clear your cache before logging in.

Please note both steps must be completed for consideration.

All applications must be received by Tuesday, June 20, 2023 5 PM Eastern Time.

The Research Fellowship Cohort 2 application is now CLOSED.

Informational Webinar 

The Research Fellowship Cohort 2 had 2 Informational Webinar on May 10 and July 7, 2023.

To watch the May 10 recording, please click here. (Passcode: h%h7#1%g)

To watch the July 7 recording, please click here

Frequently Asked Questions

Collections of answers to our most Frequently Asked Questions about the AIM-AHEAD  Fellows Program are available here

Please visit this page regularly as we will continue to add additional answers.

 

Questions regarding the Fellows Program may be directed to:

https://helpdesk.aim-ahead.net/ticket/create/research_fellowship

 

Program Directors:

  • Director: Paul Avillach, MD, PhD, Harvard Medical School
  • Co-Director: Gloria Washington, PhD, Howard University
  • Co-Director: Wyatt Bensken, PhD, OCHIN
  • Co-Director: Nawar Shara, PhD, MedStar Health Research Institute 

 

AIM-AHEAD Research Fellows Cohort 1 - AIM-AHEAD Annual Conference August 2023
AIM-AHEAD Research Fellows Cohort 1 - AIM-AHEAD Annual Conference August 2023
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