CLINAQ Fellowship Program Call For Mentors
AIM-AHEAD Clinicians Leading Ingenuity IN AI Quality (CLINAQ) Fellowship Program is recruiting mentors for Year 1 Fellows.
AIM-AHEAD is excited to launch several new training programs, each designed to further develop a diverse workforce of researchers who are proficient in AI/ML and eager to address unmet needs in underrepresented communities. Postgraduates, graduate students, postdocs, healthcare workers, and all early-career researchers are encouraged to apply! You may apply to multiple training programs, but if accepted into more than one, you can only participate in one.
Select from the program title links below to read the Call for Applications and to apply now!
This program seeks to promote researcher diversity in AI/ML by training individuals from diverse backgrounds in AI/ML data analysis, and applying their expertise to benefit underrepresented communities.
Application Deadline: November 18, 2024, 11:59 p.m. Eastern Time
An 8-month program for postgrads, postdocs, early-career faculty, and professionals. Trainees will utilize AI-READI data, AIM-AHEAD’s Data Science Training Core, and the AIM-AHEAD Connect Platform.
Application Deadline: November 18, 2024, 11:59 p.m. Eastern Time
If you still have questions after reading through the Call for Applications, please reach out to the AIM-AHEAD Training Programs HelpDesk for more assistance.
An intensive 8-month training program in advanced data analysis developed by Bridge2AI to equip trainees to conduct in-depth analysis of large datasets essential for cutting-edge biomedical and socioeconomic research.
Application Deadline: November 18, 2024, 11:59 p.m. Eastern Time
Traineeship in advanced data analysis using NCATS data, the N3C Data Enclave, and AIM-AHEAD’s Data Science Training Core to conduct data analysis for cutting-edge biomedical and socioeconomic research.
Application Deadline: November 18, 2024, 11:59 p.m. Eastern Time
The AIM-AHEAD ScHARe Training Program is designed to increase the diversity of researchers skilled in AI/ML by providing training on the utilization of AI for population health research, leveraging the ScHARe Terra workspaces.
Application Deadline: November 18, 2024, 11:59 p.m. Eastern Time
AIM-AHEAD Clinicians Leading Ingenuity IN AI Quality (CLINAQ) Fellowship Program is recruiting mentors for Year 1 Fellows.
AIM-AHEAD leadership welcomed 2024-25 awardees for the start of the Year 3 program.
AIM-AHEAD is proud to announce the awardees for our Year 3 programs for the 2024-25 funding cycle. View the preliminary list of AIM-AHEAD Year 3 programs and award recipients.
AIM-AHEAD Program for Artificial Intelligence Readiness (PAIR) celebrated the beginning of their Cohort 1 Phase 2 program.
The five training programs will engage a diverse workforce of researchers committed to gaining proficiency in AI/ML data analysis that benefits communities under-represented in biomedical research.
New AIM-AHEAD/AIHEC Partnership formed to increase Tribal Colleges and Universities (TCUs) representation in AI/ML curriculum development and implementation.
Interested researchers can find out more about AIM-AHEAD PAIR's Cohort 2 Call for Proposals.
Join us for the launch of the AIM-AHEAD Connect Training Webinar Series!
Join Georgetown and AIM-AHEAD to explore health data resources, standards, and interventions.
Learn about program details, application process, and engage in a Q&A session with program leads and instructors.
Find out full training and application details on this program that helps professionals gain AI/ML skills in health data and advance research for underserved communities.
Program directors will provide details on the AIM-AHEAD Bridge2AI AI-READI traineeship and the application process.
Stay up to date with our initiatives and funding opportunities.
Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) is a program funded by the National Institutes of Health that aims to enhance the participation and representation of researchers and communities currently underrepresented in the development of AI/ML models and to improve the capabilities of this emerging technology. Read More
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