Call for Applications

AIM-AHEAD FHIR (Fast Healthcare Interoperability Resources) Collaborative Training Program

AWARD DETAILS

Despite growing recognition of the importance of health data interoperability, the adoption and proficient use of Fast Healthcare Interoperability Resources (FHIR®) remain limited across clinical, research, and technology settings. This situation presents a barrier to realizing the full potential of clinical data, as fragmented and non-standardized data systems continue to challenge scalable innovation. There is an urgent need to increase the number of individuals with experience using FHIR, as well as to sustain both the technical expertise and knowledge required to champion FHIR adoption within their organizations and across their clinical, research, and/or technology research communities.

The overall aim of the AIM-AHEAD FHIR Collaborative Training Program is to train a multidisciplinary cohort of individuals from academia, industry, healthcare organizations, and community-based organizations in accelerating and sustaining FHIR adoption across various healthcare and research settings. We envision the program building a national network of FHIR champions composed of researchers, clinicians, software developers, informaticists, and other healthcare providers from various disciplines. The result will be the development of a cohort of well-trained and functional FHIR users able to appropriately leverage this technology to drive basic, clinical, social, and behavioral sciences.

PURPOSE OF THE AIM-AHEAD FHIR COLLABORATIVE TRAINING PROGRAM

The purpose of the AIM-AHEAD FHIR Collaborative Training Program is to train, accelerate, and sustain workforce development in FHIR and related technologies in various disciplines from academia, industry, and community-based organizations. We aim to expand and empower a skilled workforce, including researchers, practicing clinicians, healthcare providers, developers, informaticists, and graduate students, that is proficient in the FHIR standard, its practical applications, and its implementation, with a focus on research, innovation, and quality improvement. The AIM-AHEAD FHIR Collaborative Training Program will not only equip trainees with FHIR skills but also foster a culture of interdisciplinary collaboration, laying the groundwork for a more seamless integration of FHIR within basic, clinical, social, and behavioral sciences.

There are three tracks for the AIM-AHEAD FHIR Collaborative Training Program, and all learning will be 100% online. Only Track 3 participants are expected to attend the in-person AIM-AHEAD conference in July 2026.

All tracks will run concurrently.

Track 1 will provide trainees with an understanding of how FHIR could accelerate health data access and use, with a focus on research applications. This track covers the background and context of FHIR, available data and tools, and examples of research using FHIR.

Who should apply for Track 1: Those looking for an overview of FHIR and related technologies, including research applications, with a limited time commitment should apply to Track 1. Track 1 trainees are expected to spend up to 30 hours over four weeks.

Track 2 will provide more technical depth compared to Track 1, tailored for each trainee based on their role: researcher, informaticist, software engineer/developer, clinician scientist, clinical resident/fellow, or graduate student. Trainees who complete Track 2 will gain technical understanding of the approaches and technologies introduced in Track 1, as well as how FHIR fits into the broader health data ecosystem.

Who should apply for Track 2: Those who are interested in gaining a more in-depth, technical understanding of FHIR and related technologies and on average are able to spend approximately 6 hours per week on the program, but are not interested in working hands-on with FHIR as part of the training or serving as a FHIR trainer in the future should apply to Track 2.

Track 3 includes the content from Track 2, plus additional hands-on experience with FHIR and related technologies. Trainees who complete Track 3 will therefore both understand and apply these technologies, with the goal of preparing trainees to use, and to train others to use, these technologies for real-world use cases in their institutions.

Who should apply for Track 3: Those interested in the content from Track 2 and who are interested in gaining additional hands-on experience using these technologies should apply for Track 3. Trainees in Track 3 will also build their ability to train others at their institution on using these technologies. On average, Track 3 trainees are expected to approximately spend 12 hours per week on the program.

OVERVIEW OF AIM-AHEAD

The National Institutes of Health's AIM-AHEAD program has established mutually beneficial, coordinated, and trusted partnerships to enhance the capabilities of researchers and communities in the development of artificial intelligence and machine learning (AI/ML) models and to expand the capabilities of this emerging technology, beginning with electronic health records (EHR) and extending to other data sets to address health outcomes.

The rapid increase in the volume of data generated through EHR and other biomedical research presents exciting opportunities for developing data science approaches (e.g., AI/ML methods) for biomedical research and improving healthcare. Many obstacles hinder more widespread use of AI/ML technologies, such as the cost, finite capacity for widespread application, and limited access to adequate infrastructure, resources, and training. Additionally, lack of both extensive data and researchers in the AI/ML field heightens the risk of creating and perpetuating reliability and performance limitations of the algorithms that adversely impact AI/ML outcomes. Many institutions have the potential to contribute expertise, data, and cutting-edge science but may lack financial, infrastructural, and data science training capacity to apply AI/ML approaches to address research questions of interest to them.

The National Institutes of Health (NIH) is committed to leveraging the potential of AI/ML to accelerate the pace of biomedical innovation, while prioritizing and addressing the complex drivers of health outcomes. These objectives require an innovative and transdisciplinary framework that transcends scientific and organizational silos. Establishment of mutually beneficial and trusted partnerships can enhance the participation and representation of researchers and communities with limited current expertise in AI/ML modeling and application, and improve the capabilities of data curation and this emerging technology.

AIM-AHEAD North Stars

Applications to the AIM-AHEAD FHIR Collaborative Training Program must be aligned with one or more of the AIM-AHEAD North Stars:

North Star 1: Develop an AI/ML workforce.
North Star 2: Increase knowledge, awareness, and national-scale community engagement and empowerment in AI/ML.
North Star 3: Use AI/ML to improve behavioral health, cardiometabolic health, and cancer.
North Star 4: Build community capacity and infrastructure in AI/ML to address community-centric health issues.

Additional information about the North Stars may be found on the AIM-AHEAD website (https://www.aim-ahead.net/)

The AIM-AHEAD Coordinating Center (A-CC) is a consortium of institutions and organizations from all stakeholder groups (academic institutions, community organizations, private businesses, non-profit, and healthcare organizations) across the nation. The (A-CC) consists of 4 Cores:

1. The Leadership/Administrative Core leads the A-CC, recruits and coordinates consortium members in the areas of project management, partnerships, stakeholder engagement and outreach to develop talented AI/ML researchers in health research. It also establishes trusted relationships with key stakeholders to enhance the volume and quality of data used in AI/ML research.
2. The Data Science Training Core assesses, develops, and implements a robust data science training curriculum and workforce development resources in AI/ML.
3. The Data and Research Core addresses research priorities and needs by linking and preparing multiple sources and types of research data. To accomplish its mission, the Data and Research Core facilitates the extraction and transformation of data from EHR and on lifestyle contributors for health research use.
4. The Infrastructure Core assesses data, computing and software infrastructure models, tools, resources, data science policies, and AI/ML computing models to facilitate AI/ML and health research. It also establishes pilot data and analysis environments to accelerate overall A-CC aims.

PROGRAM DETAILS

Abbreviations:  

API: Application Programming Interface
CDEs: Common Data Elements
CDS: Clinical Decision Support
CDS Hooks: Health Level Seven International® (HL7®) specification managed by the HL7 CDS work group
CQL: Clinical Quality Language
EHR: Electronic Health Records
FHIR: Fast Healthcare Interoperability Resources
OMOP: The Observational Medical Outcomes Partnership
SMART on FHIR: Substitutable Medical Applications, Reusable Technologies on FHIR

PROGRAM GOALS & TIMELINE

Applicants must apply for only one track.

Participants in the FHIR Program will engage in specialized tracks that align with their interests and career goals, ensuring a tailored experience that supports professional development and impact in research. Participation will empower trainees to make significant contributions in the areas of data science, research, and infrastructure within the health sector.

Before selecting a track, applicants are encouraged to carefully review the objectives and requirements of each path to determine which one best aligns with their background and aspirations. This approach ensures that every trainee can maximize their learning and contribute meaningfully to the overarching mission of AIM-AHEAD.

All Tracks run concurrently, and all trainees will complete Track 1 simultaneously at the beginning of the Program. Trainees in Track 2 and 3 will continue after Track 1 is complete, and will receive the same didactic materials. Additionally, Track 3 trainees will apply the technologies covered in Track 2 to build a proof-of-concept or prototype using the technologies covered in the didactic materials. Track 3 trainees will also receive 1:1 coaching from AIM-AHEAD, and will participate in “train the trainer” activities to build their capacity to train others on these technologies in the future.

Trainees in Track 3 will apply FHIR and related technologies covered in the training by building a “hands-on project” consisting of a technical proof-of-concept or prototype that utilizes these technologies, and is within one of the Focus Areas identified below. Trainees without ready access to the necessary data resources at their institution will use synthetic data (e.g., from the Synthea project) or data from other publicly-available de-identified FHIR data sources. No IRB review will be required for projects using synthetic or de-identified data sources. The hands-on projects will be completed by groups of Track 3 trainees utilizing a team‑science approach, bringing the necessary clinical and technical expertise together on the same team. All Track 3 trainees are expected to participate in the hands-on technical development of their team’s proof-of-concept/prototype, and Track 3 trainees with less prior technical experience will be expected to provide other necessary subject-matter expertise (e.g., clinical expertise) for their team.

The “Expected Average Number of Hours of Training” in the table above reflects the minimum time needed for successful completion of activities for a given Track (e.g., the 12 hours/week of expected average time for Track 3 includes time for technical training, the hands-on project, meeting with the coach, etc.). However, actual time may vary depending on factors including the chosen engagement activities for all Tracks and the hands-on project scope for Track 3.

FOCUS AREAS (Tracks 2 & 3)

Trainees in Tracks 2 and 3 will receive training specific to the following Focus Areas. 

Focus Area 1: Building Clinical Decision Support Tools with FHIR

This training covers how the use of FHIR standards, Application Program Interfaces (APIs), and “SMART on FHIR” apps to create tools that assist healthcare providers in making evidence-based decisions. Participants will learn how CDS Hooks (tools that let apps share smart alerts or suggestions within EHR) and FHIR data models can be used to integrate these tools directly into EHR systems.

Focus Area 2: Applying AI/ML with FHIR Data

This training examines how FHIR data can power AI/ML models in healthcare. Participants will learn how to access and prepare FHIR data for tasks like risk prediction, natural language processing, and medical imaging analysis.

Focus Area 3: Working with FHIR Data for Health Outcomes/Population Health

This training covers how to use FHIR Bulk Data APIs to gather data across patient groups for public health, quality improvement, and research. Participants will practice working with FHIR data in data science environments such as R or Python.

TRAINEE EXPECTATIONS

PROGRAM ACTIVITIES 

The following table outlines the key activities participants are expected to complete throughout the program. Each track offers unique requirements designed to support learning, engagement, and professional development. Review your track’s activities carefully to stay on course for success.

* Trainees who play an active part in the AIM-AHEAD community will participate in at least one community activity per month. Example activities include but are not limited to: attend and participate in AIM-AHEAD sponsored community events; use AIM-AHEAD Connect platform to exchange ideas, seek advice, and share updates of research progress; contribute AI methodologies, statistical programming, and other tools; volunteer for Q&A sessions; moderate panels; increase visibility of AIM-AHEAD through digital platforms and professional networks; give feedback for improvement of AIM-AHEAD operations; share resources; and contribute to domain-specific activities.

PROGRAM MILESTONES 

The program's milestones represent key achievements that trainees are expected to reach throughout their participation in the FHIR Program. These milestones are designed to ensure that each participant gains foundational knowledge of FHIR, CDEs, and related health data technologies, while also engaging with peers and experts through interactive events. Achieving these milestones will help trainees build essential competencies and foster connections within the broader health data research community. The milestones outlined below provide a structured path for learning, collaboration, and professional growth during the program.

Key Milestones

Important Notice

Consistent with NIH practice and applicable law, AIM-AHEAD programs may not use the race, ethnicity, or sex of prospective program participants or faculty as an eligibility or selection criteria. The race, ethnicity, or sex of candidates will not be considered by AIM-AHEAD in the application review process or when making funding decisions.

Eligible Organizations

Higher Education Institutions

• Public/State Controlled Institutions of Higher Education.
• Private Institutions of Higher Education.

Nonprofits

• Nonprofits with 501(c)(3) IRS Status.
• Nonprofits without 501(c)(3) IRS Status.

For-Profit Businesses/Organizations

• Small Businesses.
• For-Profit Organizations (Other than Small Businesses).

Local Governments

• State Governments.
• County Governments.
• City or Township Governments.
• Special District Governments.
• Indian/Native American Tribal Governments (Federally Recognized).
• Indian/Native American Tribal Governments (Other than Federally Recognized).

Other

• Independent School Districts.
• Public Housing Authorities/Indian Housing Authorities.
• Native American Tribal Organizations (other than Federally recognized tribal governments).
• Faith-based or Community-based Organizations.
• Regional Organizations.

The applicant’s organization must be a domestic institution/organization located in the United States and its territories.

Foreign Institutions

• Non-domestic (non-U.S.) Entities (Foreign Institutions) are not eligible to apply.
• Non-domestic (non-U.S.) components of U.S. Organizations are not eligible to apply.
• Foreign components, as defined in the NIH Grants Policy Statement, are not allowed.

APPICANTS ELIGIBILITY CRITERIA

1. 1. Candidates must be U.S. Citizens, Permanent Residents, or Non-Citizen U.S. Nationals.
      • U.S. Citizen: Any individual who is a citizen of the United States by law, birth, or naturalization.
      • Permanent Resident: A standing given to United States immigrants/non-citizens who can legally reside in the United States in perpetuity.
        • The applicant must have their permanent residency at the time of application (no later than September 26, 2025).
      • Non-Citizen National: A person born in an outlying possession of the United States on or after the date of formal acquisition of the United States at birth.
      • Accepted candidates must be able to submit a W-9 tax form.
      • AIM-AHEAD Coordinating Center personnel (hubs/cores/offices) are eligible to participate in the Training Programs (listed above), but will not receive a stipend or travel allowance.
      • Federal employees are eligible to participate in the Training Programs (listed above), but will not receive a stipend or travel allowance.
   2. Applicants Not Eligible
      • Individuals on temporary visas (F1, J1, H1, etc.) are not eligible.
      • Current and former AIM-AHEAD awardees who received funding from AIM-AHEAD programs within the last 3 years are not eligible.
   3. Education
      • Successful completion of an undergraduate or graduate course in probability and statistics or completion of other college-level mathematics coursework.
      • Applicants can be post-baccalaureate or graduate students, healthcare providers, medical students or residents, allied health trainees, informaticists, software engineers, administrators, early-career investigators, or early-career employees of non-academic institutions as defined in the “Eligible Organizations” section above. Applicants must hold at a minimum a bachelor’s degree 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, nursing, social work).
        • Public health (epidemiology, biostatistics, health administration, clinical implementation specialists).

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. 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.

Required Format

• Arial font, minimum 11 points; margins at least 0.5 inches (sides, top, and bottom).
• Single-spaced lines and consecutively numbered pages.
• Submit a single PDF document to the InfoReady application portal: https://aim-ahead.infoready4.com/#competitionDetail/1998637.

Required Elements of the Proposal

Profile Information

• Provide your name, organization, department, position title, research area, email address, and profile web page.
• Please answer all profile questions on the InfoReady application.

Letters of Support

• One signed letter of support from the applicant's supervisor is required. The letter of support must include the referring individual’s contact information (full name, position title, organization, email/phone number) and signature and must be on the letterhead of the supervisor’s organization.
• In addition to the supervisor’s letter, a minimum of one letter of recommendation is required (a second letter of recommendation is optional) from faculty who taught the applicant or from an individual who can attest to the applicant's preparedness, aptitude, and rationale for advanced data analysis training. Letters of recommendation should highlight relevant skills and accomplishments. Each letter must include the referring individual’s contact information (full name, position title, organization, email/phone number) and signature, and must be on the letterhead of the referring individual’s organization.
• For applicants who hold faculty positions (assistant, associate, or full professor), only one letter is required, from the department chair or equivalent.
• Letters must include either a handwritten signature (scanned or photographed) or a digital signature. Typed signatures will not be accepted.

Biographical Sketch of the Applicant

• The applicant’s NIH biosketch or CV (not exceeding 5 pages) is required. NIH biosketch form: https://grants.nih.gov/grants/forms/biosketch.htm.
• Template: Traineeship Biosketch.

Statement of Rationale for Pursuing Training

Provide a personal statement of no more than 750 words addressing the following:

• All tracks:  Describe what you hope to accomplish through the AIM-AHEAD FHIR Collaborative Training Program, including: what specific knowledge, tools, or capabilities you hope to gain (e.g., FHIR fundamentals, interoperability skills, hands-on project experience, research workflows); how this training fills a gap in your current skill set; and  why FHIR is relevant to your academic, clinical, or research interests.
• All tracks: Provide your rationale and need for AIM-AHEAD FHIR training and acquiring these skills. Why do you specifically need FHIR training at this stage of your career or education? How does lacking these skills limit your current work or future goals? Why are you interested in participating in this particular program? 
• All tracks: Explain how you plan to apply the training to achieve your long-term interests and objectives. How will FHIR competency support your career trajectory (e.g., clinical informatics, data science, medicine, public health, population health, health outcomes, health professions, research, innovation)? How do you expect the training to influence your community, institution, or field?
• All tracks: Describe your interest in healthcare data, EHRs, data standardization, programming, clinical data analysis, biomedical science, public health, and/or cloud-based computation.
• Tracks 2 & 3: Discuss your exposure to healthcare data in clinical, academic, or research contexts, data cleaning, extraction, coding or analysis, informatics course work, any programming experience (basic or advanced). Concrete examples are stronger than general statements.
• Track 3 only: Demonstrate your experience in the following via coursework, research, or practical experience: clinical informatics; clinical data management, manipulation, or analytics or research utilizing health data. Show familiarity with real-world health data challenges.
• Track 3 only: Highlight your enthusiasm for collaborative problem-solving; past teamwork experiences (research, engineering, clinical, academic projects) and why you want to work on a joint FHIR-based hands-on project.

Tips for writing a strong personal statement:

• Keep it personal—focus on your goals and motivations.
• Be concise. Avoid repeating the same idea in different words.
• Use specific examples rather than broad descriptions.
• Make sure every sentence relates to what the program is looking for (interoperability, informatics, training needs, long-term impact).
• Stay within the 750-word limit.

APPLICATION SUBMISSION USING AIM-AHEAD CONNECT AND INFOREADY PLATFORM

The applications will be evaluated based on the following criteria. However, the evaluations will be based on the criteria relevant to each track. For example, Track 1 applicants are not expected to have prior technical experience, and lack of such experience will not be evaluated negatively.

1. Articulation of Expectations and Reasons for Participation: The applicant must clearly articulate personal expectations and motivations for joining the program. The applicant should communicate the necessity and significance of the training for their professional development (all Tracks). 
2. Motivation for Training: The applicant should describe their relevant background, professional experience, or academic qualifications that support their readiness for this program, and demonstrate the motivation and potential to actively participate in and derive meaningful benefits from the training (all Tracks).
3. Long-term Application of Training: The applicant should provide specific and feasible plans to apply FHIR training in their research or professional development. Specify detailed strategies that indicate a commitment to integrating the training into their long-term career or academic objectives (Track 3).
4. Support from Supervisors or Mentors: The letter(s) of support should provide 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 (all Tracks).
5. Reference(s) and Assurance of Success: The letters of reference should provide 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 (all Tracks).
6. Community Engagement and Collaboration. The applicant must express a readiness to actively engage with the AIM-AHEAD community. There should be a demonstrated commitment to contributing to communal resources, empowering new users, and promoting a culture of cross-disciplinary collaboration within the community (all Tracks).

AVAILABLE SUPPORT FROM AIM-AHEAD FUNCTIONAL CORES

The AIM-AHEAD FHIR Collaborative Training Program awardees will receive support from the following A-CC cores:

DATA AND RESEARCH CORE

The Data and Research Core will work with the awardees:

• To help prioritize data curation and linking opportunities that will be of the highest value to AIM-AHEAD Consortium members.
• To provide guidance and lessons learned on data use agreements necessary to participate as data contributors to AIM-AHEAD-sponsored programs.
• To provide feedback on proposed data governance structures and processes.

INFRASTRUCTURE CORE

The Infrastructure Core will provide the awardees:

• AI/ML Assessment Tool and Maturity Model to pre-evaluate applicants or awardees and tailor the program based on their current capabilities and resources.
• Open-source data and AI/ML tools:
  • Team of solution architects, data scientists, and software engineers to provide training and mentorship.
  • Administrative and operational support models.

AI-OPTIMIZATION SUB-CORE

The AI-Optimization Sub-Core will support the awardees by:

• Providing a central resource for discussing and exploring AI optimization matters within the AIM-AHEAD program.
• Offering access to expert insights, engagement in meaningful conversations, and resources to guide AI decision making.

DATA SCIENCE TRAINING CORE (DSTC)

The Data Science Training Core will support the awardees by:

• Identifying training needs.
• Recommending customized training modules.
• Supporting Helpdesk requests related to data science training.
• Synergizing with ongoing DSTC programs such as practicum, professional development, and outreach.

Applicants should expect notification of their acceptance status on Wednesday, February 11 2026. Accepted applicants will receive an invitation from PaymentWorks requesting:

• A valid tax ID (either an EIN or SSN) via W9 for U.S. vendors.
• A Bank Validation file for ACH/EFT or wire payments (https://community.paymentworks.com/payees/s/article/What-Is-A-Bank-Validation-File).

PROGRESS AND POST-AWARD REPORTING

Each trainee is responsible for completing milestones by the indicated due dates. There are baseline evaluations, mid-point evaluations, and post-program evaluations that are mandatory for completion. Trainees must engage in all requested reporting requirements before, during, and after the program. 

If trainees do not complete the required evaluations and key milestones (see Key Milestones table above) by the indicated due dates, they may not be eligible to receive their stipend. Completion of all mandatory evaluations and engagement in reporting requirements is necessary for stipend disbursement.

TRAINEE STIPEND AND BENEFITS 

The AIM-AHEAD program is committed to supporting its trainees by offering competitive stipends and a comprehensive range of benefits. These financial incentives are designed to recognize the dedication and effort of participants, while also assisting them in meeting important milestones throughout their training. In addition to stipends, selected tracks may offer allowances to help cover travel and accommodation expenses for program-related events. Detailed information about stipends and benefits for each track is provided below.

There will be an informational webinar on December 17, 2025 — 2:00 p.m. Central Time.

Register here for the webinar.

Frequently Asked Questions

Please refer to the Frequently Asked Questions document before creating a Helpdesk ticket.

Link for frequently asked questions

Helpdesk

If your question is not answered in the above FAQ document, please create a Helpdesk ticket using the link below.

FHIR Helpdesk

AIM-AHEAD FHIR Collaborative Training Program Directors 

• Usha Sambamoorthi, PhD, The University of North Texas Health, Fort Worth, TX
• Damaris Javier, PhD, The University of North Texas Health, Fort Worth, TX
• Tonychris Nnaka, PhD, The University of North Texas Health, Fort Worth, TX
• Jamboor K. Vishwanatha, PhD, The University of North Texas Health, Fort Worth, TX