Call for Applications

AIM-AHEAD Bridge2AI AI-READI Training Program

AIM-AHEAD Traineeship in Advanced Data Analysis using the Bridge2AI AI-READI database

Program Description

The application of artificial intelligence and machine learning (AI/ML) to large datasets is dramatically expanding the capacity for hypothesis testing impacting the biomedical and socioeconomic domains. However, underrepresented communities, particularly those at heightened risk of socioeconomic and health disparities, are not receiving AI/ML’s benefits. There is a need for increased use of NIH Common Fund datasets among diverse communities of researchers. AI-READI is one of the Grand Challenges in the NIH Common Fund-supported Bridge2AI Program and will partner with AIM-AHEAD to provide training opportunities centered on the AI-READI dataset to diverse researchers (see https://aireadi.org/). Training a diverse workforce of researchers proficient in the application of AI/ML represents an opportunity to address a critical unmet need by extending the benefits of AI/ML to underrepresented, at-risk communities. 

The overall goal of the AIM-AHEAD Bridge2AI AI-READI Training Program is to expand AI-READI data access through engagement and training, including use of AI/ML in analysis and a train-the-trainer model, and allowing AIM-AHEAD trainees to conduct novel research at the intersection of AI/ML and health disparities with a multi-modal array of data elements from a diverse cohort.

To accomplish this objective, an initial cohort of 25 diverse professionals committed to applying AI/ML to benefit underrepresented communities will complete an intensive 8-month program in advanced data analysis developed by Bridge2AI and utilizing the resources of the AI-READI data and AIM-AHEAD’s Data Science Training Core. Completing the training will equip the motivated professional to conduct the in-depth analysis of large datasets essential for cutting-edge biomedical and socioeconomic research.

Program Objectives

The following are the objectives for trainees upon completing the program:

An important secondary outcome is that these activities will result in early trainee feedback regarding the Bridge2AI AI-READI dataset, enabling immediate iterative improvement to maximize its wider trainee utilization and integration with other Common Fund resources.

A partnership between AIM-AHEAD and Bridge2AI AI-READI offers a training program to allow for further development of a diverse workforce of researchers who are proficient in AI/ML and eager to address unmet needs in underrepresented communities. This training program will reduce barriers and increase researcher diversity in AI/ML by engaging AIM-AHEAD trainees with procuring access to Bridge2AI AI-READI data and providing training regarding analyses of these data. 

The program aims to engage, sign up, and train underrepresented researchers and students from AIM-AHEAD to use the AI-READI Fairhub.io platform and the AI-READI dataset. The Artificial Intelligence Ready and Equitable Atlas for Diabetes Insights (AI-READI) project seeks to create a flagship ethically-sourced dataset to enable future generations of artificial intelligence/machine learning (AI/ML) research to provide critical insights into type 2 diabetes mellitus (T2DM), including salutogenic pathways to return to health (aireadi.org). The first version of the dataset was released on May 3, 2024 and will therefore be available for program participants to use during the proposed award period. This activity will adopt and tailor training programs for AIM-AHEAD needs. AIM-AHEAD and AI-READI will deliver a training and mentorship experience using the AIM-AHEAD Connect platform for 25 AIM-AHEAD trainees, comprising graduate students, postdocs, early-career faculty, healthcare professionals, and non-academic professionals from underrepresented populations. 

Trainees will receive hands-on training on the Bridge2AI AI-READI data and leverage the data and tools to write a research proposal, putting their new skills to work in real-life situations and novel research. 

Training will include:

• • Foundational AI/ML Training-AI Essentials for Healthcare, with a focus on:
    • Identifying appropriate AI tools for different contexts and applications in healthcare setting
    • Identifying the right AI tool for different challenges and opportunities
    • Managing and launching AI projects in healthcare
  • Basic Biomedical Research concepts and Human Subjects Research Protection
  • Foundations of ethical research and ethical considerations in AI-READI
  • Mentorship with a mentor with expertise in AI, health equity, and/or community engagement 
  • Diversity in Research
  • Stigma and Stigmatizing Research
  • Biology and Society
  • Group Harms and Cultural Competence
  • Social Responsibility in Research
  • Overview of the domains in AI-READI, including review of the healthsheets metadata, the dataset structure specifications, and details about each data domain (e.g. overview of diabetes, introduction to retinal imaging, introduction to EKG data, environmental sensor data, etc.)
  • Analyzing Bridge2AI AI-READI data including
    • Working with OMOP data
    • Creating Cohorts
    • Creating concept sets
    • Analyzing waveform data
    • Analyzing imaging data
  • R, Python, Jupyter notebooks, and model development.
  • Asynchronous material is available and will be supplemented with live training and office hours

Training Implementation will include:

• 4 virtual workshops provided by AIM-AHEAD Data Science Training Core
• Attestation statements
• Developing feasible and detailed research proposals to enter into Fairhub. This will involve at least 1 live workshop to offer guidance
• Developing abstracts or manuscripts based on research projects completed using AI-READI data. This will involve multiple live lectures to go over the domains of the dataset, the AI-READI file structure, and how to work with the data for analysis in projects

This robust educational framework is designed to empower the next generation of healthcare professionals with the tools and knowledge necessary to drive forward the field of AI in medicine. Having received advanced practical training in AI/ML Cloud Computing, AI/ML Notebooks, AI/ML Principles, and Knowledge of AI-Ready Standards, trainees completing this program will be well-prepared to harness AI/ML approaches to conduct hypothesis-driven analysis of complex datasets. They will also have specific familiarity and experience with working with the Bridge2AI/AI-READI datasets, which will serve as concrete data resources for their current and future use. The trainees will join the community of AI/ML professionals passionately committed to extend the benefits of AI/ML to communities underrepresented in biomedical research.

-- Applications are due by Monday, November 18, 2024, at 11:59 p.m. Eastern Time. 

-- Training through AIM-AHEAD Connect will begin on January 15, 2025. 

Trainee Expectations

• • Attend all training sessions, both synchronous and asynchronous, including workshops, webinars and seminars
  • Work on the program an average of at least 5-8 hours per week
  • Engage with an AIM-AHEAD Mentor (to be assigned through the program)
  • Engage in learning communities and peer networking
  • Access the Bridge2AI AI-READI data
  • Complete the provided training related to R, Python, and Jupyter Notebook, available via AIM-AHEAD Connect
  • Complete the onboarding process including an Orientation
  • Utilize Office Hours and Concierge Services 
  • Utilize AIM-AHEAD HelpDesk support 
  • Present a work-in-progress research poster at a Bridge2AI Meeting in spring 2025 and the AIM-AHEAD Annual Meeting in summer 2025
  • Generate an abstract suitable for submission to a conference, and/or a manuscript suitable for peer-reviewed publication
  • Play an active part in the AIM-AHEAD community

Data Use Agreement

This agreement outlines the program’s expectations for researchers who use the Bridge2AI AI-READI data. Researchers should be able to complete data access requirements for the Bridge2AI AI-READI dataset, including reviewing and signing a data usage license, completing relevant pre-requisite training, completing attestation statements, and providing information about intended research uses. These access requirements are outlined on docs.aireadi.org and will be covered in this program’s instructional content as well. Currently, access to the Bridge2AI AI-READI dataset is limited to individuals with an .edu email account. However, if an individual has strong interest and does not currently have an .edu email account, the program can potentially facilitate access.

Trainees Will Receive

• • A stipend totaling $8,000, plus a $2,000 allowance to attend the AIM-AHEAD and Bridge2AI Annual Meetings in 2025
  • Support and guidance from an experienced AIM-AHEAD mentor
  • Support from the AIM-AHEAD Data Science Training Core
  • Direct 1:1 guidance, virtual office hours, helpdesk support and concierge services supporting projects using AI-READI data
  • Training on:
  • Basic biomedical research concepts and human subjects research protection
  • Foundations of ethical research and ethical considerations in AI-READI
  • Diversity in Research
  • Stigma and Stigmatizing Research
  • Biology and Society
  • Group Harms and Cultural Competence
  • Social Responsibility in Research
  • Overview of the domains in AI-READI, including review of the healthsheets metadata, the dataset structure specifications, and details about each data domain (e.g. overview of diabetes, introduction to retinal imaging, introduction to EKG data, environmental sensor data, etc.)
  • R, Python, Jupyter notebooks, and model development.
  • Analyzing Bridge2AI AI-READI data including
    • Working with OMOP data
    • Creating Cohorts
    • Creating concept sets
    • Analyzing waveform data
    • Analyzing imaging data

Trainee Program Stipend

Each trainee will receive a stipend of $8,000 which will be disbursed in four installments based on trainee completion of required milestones. Each trainee will also be provided an allowance of $2,000 to cover the cost of airfare, hotel accommodations, local transportation and per diem to attend Annual Meetings for AIM-AHEAD and Bridge2AI in 2025.*

*Trainees may apply to multiple AIM-AHEAD training programs and fellowships, but if accepted into more than one, they must select only one AIM-AHEAD training program to participate in per funding cycle. Additionally, AIM-AHEAD-funded Coordinating Center Personnel (MPIs, PIs, Co-Investigators, other personnel) are eligible to apply, but if accepted, they will not receive the stipend and allowance.*

Trainee Mentorship

Each awarded trainee will receive mentorship from experienced, skilled investigators selected from AIM-AHEAD core members, who will guide the trainee in developing testable hypotheses using AI-READI data. The online mentoring platform AIM-AHEAD Connect (https://connect.aim-ahead.net) will be used to match mentors with awarded trainees and for mentor/trainee engagement and progress tracking.

1. Applicants must be:
   1. U.S. Citizens, Permanent Residents, or Non-Citizen U.S. Nationals
      • US Citizen: An individual who is a citizen of the United States by law, birth or naturalization (https://www.law.cornell.edu/definitions/uscode.php?width=840&height=800&iframe=true&def_id=42-USC-630966247-802284531&term_occur=1&term_src=title:42:chapter:99:section:9102)
      • Permanent Resident: An immigrant/non-citizen who can legally reside in the United States in perpetuity (https://www.law.cornell.edu/wex/lawful_permanent_resident_(lpr))
      • Non-Citizen National: A person born in an outlying possession of the United States on or after the date of formal acquisition by the United States (https://www.law.cornell.edu/uscode/text/8/1408)
   2. Able to submit Form W-9 (Request for Taxpayer Identification)
   3. Affiliated with one of the following entities:
      • Higher Education Institutions
        • Public/State Controlled Institutions of Higher Education8
        • Private Institutions of Higher Education
        Individuals affiliated with the following types of Higher Education Institutions are always encouraged to apply:
        • Hispanic-serving Institution
        • Historically Black Colleges and Universities (HBCUs)
        • Tribally Controlled Colleges and Universities (TCCUs)
        • Alaska Native and Native Hawaiian Serving Institutions
        • Asian American Native American Pacific Islander Serving Institutions (AANAPISIs)
      • Nonprofits Other Than Institutions of Higher Education
        • Nonprofits with 501(c)(3) IRS Status (Other than Institutions of Higher Education)
        • Nonprofits without 501(c)(3) IRS Status (Other than Institutions of Higher Education)
      • For-Profit Organizations
        • Small Businesses
        • For-Profit Organizations (Other than Small Businesses)
2. Education: Applicants can be post-baccalaureate or graduate students, postdoctoral fellows, medical students or residents, allied health trainees, early-career investigators, or early-career employees of non-academic institutions as defined in item 1C above. Applicants must hold at a minimum a bachelor’s degree from an accredited U.S. institution in one of the following or related fields:
   • • Physical sciences (e.g. chemistry, physics)
     • Biological or life sciences (e.g. biology, zoology, biochemistry, microbiology)
     • Mathematics or statistics
     • Data science
     • Engineering
     • Health sciences (e.g. pharmacy, psychology, health information technology, nurses, therapists, social workers)
     • Public health (epidemiology, biostatistics, health administration, clinical implementation specialists)
3. Recommended Applicant Knowledge, Skills, and Experience:

   To ensure success in the training program, applicants must already possess certain skills and experience to optimize their learning experience and better prepare them for the challenges of the program.

   • Prior programming experience
   • Basic understanding of statistics
   • A working command of English, as all training courses will be conducted in English

   Additionally, it is strongly recommended that applicants have some of the following skills and experiences to optimize their learning experience and better prepare them for the challenges of the program.

   • Successfully completed an undergraduate or graduate course in probability and statistics or completion of other college-level mathematics coursework
   • Has practical experience in coding/programming with R or Python
   • Has experience in data manipulation and management gained through coursework and/or research projects

   Introductory or refresher courses on these topics will be available to successful applicants at the start of the traineeship, via the AIM-AHEAD Connect platform.

Applications must be submitted during the open application period (10/18/24 - 11/18/24). Applications should address the requirements below and any additional questions via the Traineeship Application Form. The application should be understandable to readers from outside the applicant’s field of study and must clearly present the project aims, applicable studies already completed, methods, materials, and AIM-AHEAD engagement plan. 

Applicants must:

1. Register as a “mentee/learner” on AIM-AHEAD Connect (our Community Building platform). Your AIM-AHEAD Connect profile will allow you to log in to submit your application on the InfoReady platform. 
2. Click here to submit an application for review using the InfoReady platform.

Please use Chrome, Firefox, or Edge. Please note that both steps must be completed for consideration.

All applications must be received by November 18, 2024, at 11:59 p.m. Eastern Time.

Profile Information

• • Provide your name, organization, department, position title, research area, email address, and profile web page
  • Please address on InfoReady the profile and prior experience questions

Letters of Support

• • One signed letter of support from the applicant’s supervisor is required. The letter of support must include the referee’s contact information (full name, position title, organization, email/phone number, and signature)
  • Minimum of one letter of recommendation (one additional letter may be provided) is required from faculty who taught the applicant or from work supervisor(s) and who can attest to the applicant’s preparedness, aptitude, and rationale for advanced data analysis training. Reference(s) should highlight relevant skills and accomplishments

Academic Unofficial Transcript

Academic transcripts must be included from the applicant’s undergraduate and, if applicable, graduate programs for current students and postgraduates.

Biographical Sketch of the Applicant

The applicant’s NIH biosketch or Curriculum Vitae (CV) is required and should not exceed 5 pages.

NIH biosketch form: https://grants.nih.gov/grants/forms/biosketch.htm

Template: Traineeship Biosketch

Instructions for a Biosketch

Predoctoral Fellowship biosketch sample

Postdoctoral Fellowship biosketch sample

Statement of Rationale for Pursuing Training

Provide a personal statement of no more than 2 pages addressing the following:

• • Describe what you hope to accomplish through the AIM-AHEAD Bridge 2AI AI-READI Training Program. Provide your rationale and need for training in AI-READI data and acquiring these skills
  • Describe your familiarity with, and/or interest, in AI/ML analysis, programming, EHR, clinical data analysis, biomedical science, public health background, and/or cloud-based computation
  • Explain how you plan to apply the training to achieve your long-term research interests and objectives

A review committee comprised of AIM-AHEAD Consortium members will apply the following criteria to evaluate and prioritize applications. In assigning priority scores, reviewers will apply the standard NIH 1-9 scoring range to Criteria 1, where a score of 1 indicates highest enthusiasm, and a score of 9 indicates lowest enthusiasm, based on NIH Simplified Review Framework - https://grants.nih.gov/grants/guide/notice-files/NOT-OD-24-010.html

Criteria 1: 

1. 1. Articulation of Expectations and Reasons for Participation: Evaluate the clarity and depth with which the applicant articulates personal expectations and motivations for joining the program. Consider how convincingly the applicant communicates the necessity and significance of the training for their career or academic ambitions.
   2. Research Background and Motivation for Training: Assess the extent of the applicant’s relevant background, professional experience, or academic qualifications that support their readiness for this program. Gauge their motivation and potential to actively participate in and derive meaningful benefits from the training.
   3. Long-term Application of Training: Examine the specificity and feasibility of the applicant’s plans to apply AI/ML training in their research or professional development. Look for detailed strategies that indicate a commitment to integrating the training into their long-term career or academic objectives.
   4. Support from Supervisors or Mentors: Determine if the letter of support provides strong and unequivocal commitment from the supervisor, faculty, or mentor. It should confirm the provision of sufficient protected time for the applicant to fully engage with the training.
   5. Reference(s) and Assurance of Success: Critique the letter(s) of reference for their effectiveness in providing a persuasive argument that the applicant is well-prepared and likely to succeed in the program. The reference(s) should highlight relevant skills, accomplishments, and the applicant's capacity for advanced training.
   6. Community Engagement and Collaboration: Evaluate how well the applicant expresses a readiness to actively engage with the AIM-AHEAD community. Look for a demonstrated commitment to contributing to communal resources, empowering new users, and promoting a culture of diversity and inclusivity within the community.

Criteria 2: 

Prior Data Science Experience: Assess applicant data science experience by reviewing education, work history, programming proficiency, project involvement, and understanding of math/statistics applied in data analysis. 

To be evaluated by selecting one of the following options from a drop-down menu.

• • Beginner
  • Intermediate 
  • Expert

Applicants should expect notification of their acceptance status on Monday, January 6, 2025. Accepted applicants will receive an invite from PaymentWorks requesting:

• a valid tax ID (either an EIN or SSN) via W9 for US vendors
• to upload a Bank Validation file for ACH/EFT or Wire Payments (https://community.paymentworks.com/payees/s/article/What-Is-A-Bank-Validation-File)

If an applicant applies and is accepted into more than one AIM-AHEAD training program, they must select only one to participate in per funding cycle. Additionally, AIM-AHEAD-funded Coordinating Center Personnel (MPIs, PIs, Co-Investigators, other personnel) are eligible to apply, but if accepted, they will not receive the stipend and allowance.

More details to come

AIM-AHEAD Bridge2AI AI-READI Training Program Co-Directors

Sally Baxter, MD, MSc, Guodong (Gordon) Gao, PhD, Toufeeq Syed, PhD

Frequently Asked Questions

Please refer to the FAQs below before submitting a help desk ticket:

AIM-AHEAD Bridge2AI AI-READI Frequently Asked Questions

Please feel free to submit a help desk ticket if you have any questions:

AIM-AHEAD Training Programs HelpDesk