NIH AI-Driven Analysis of the Evolving AI Policy Landscape

Organization National Institutes of Health (NIH) Reference Code NIH-DPCPSI-CAIO-AIPolicy-2026 How To Apply Click on Apply below to start your application. An initial review of applications will occur on July 1, 2026. Thereafter, applications will be reviewed on a rolling-basis throughout the 2026 calendar year, and selections made as projects for participation become available. Description The National Institutes of Health (NIH), Office of the Chief Artificial Intelligence Office (CAIO), is offering a unique hands-on STEM learning experience for recent Post Master's or Post Doctoral applicants. During this fellowship, participants will engage in an interdisciplinary research initiative aimed at exploring innovative, agent-driven methodologies to analyze the dynamic and complex policy landscape surrounding artificial intelligence. Guided by an experienced mentor, fellows will actively contribute to the creation and refinement of automated systems designed to systematically identify, categorize, and synthesize regulatory, statutory, and legislative documents from diverse governmental and international sources. This immersive experience emphasizes hands-on learning and fosters the development of advanced analytical pipelines to evaluate newly released policy documents within the broader context of historical policy trends. Fellows will have the unique opportunity to integrate technical expertise in AI systems engineering with public policy analysis, all within a secure and collaborative research environment. What will I be doing? To foster professional growth and multidisciplinary expertise, fellows will focus on achieving the following learning objectives: • Developing Agent-Driven AI Systems: Fellows will gain practical experience designing and implementing AI systems that automate the collection, analysis, and synthesis of policy and regulatory frameworks. • Applying Advanced Analytical Tools: Using Natural Language Processing (NLP) and machine learning techniques, fellows will identify trends, deviations, and conceptual shifts across large text corpora. • Exploring AI and Public Policy Intersection: Fellows will deepen their understanding of how emerging AI technologies intersect with public policy and learn to translate technical capabilities into actionable policy insights. • Designing and Validating Computational Tools: Fellows will learn to design, test, and validate workflow tools that ensure analytical accuracy and reliability for decision-making in policy contexts. • Enhancing Scientific Communication Skills: Fellows will refine their ability to communicate complex technical findings and policy analyses through clear reports, presentations, and scholarly publications. Why should I apply? This STEM research participation program offers fellows a unique opportunity to immerse themselves in cutting-edge research at the intersection of AI and policy. Participants will explore NIH collaborative research programs, gain experience using NIH databases and analytical modalities, and learn how to identify metrics and key indicators for evaluating research initiatives. Fellows will also compare the outcomes of diverse collaborative programs and make recommendations for future initiatives based on data-driven insights, all under the guidance of an expert mentor. This fellowship is an ideal opportunity for individuals seeking to expand their expertise in AI systems, policy analysis, and interdisciplinary collaboration while contributing to meaningful advancements in research and policy development. Where will I be located? Fellows are expected to be fully engaged remotely. What financial provisions will I receive? The selected candidates will receive a monthly stipend to help offset living and other expenses during this appointment. Stipend rates are determined by NIH officials and are based on the candidate’s academic and professional background. In addition, NIH may provide a health insurance supplement to cover the monthly premium costs if you elect the ORAU/ORISE health insurance plan, as necessary. What is the length of the appointment? The appointment will initially be for one year and may be renewed annually up to an additional four years, upon recommendation of NIH and is contingent on the availability of funds. When are selections made? An initial review of applications will occur on July 1, 2026. Thereafter, applications will be reviewed on a rolling-basis throughout the 2026 calendar year, and selections made as projects for participation become available. What is the Nature of the Appointment? This program, administered by ORAU through its contract with the U.S. Department of Energy (DOE) to manage the Oak Ridge Institute for Science and Education (ORISE), was established through an interagency agreement between DOE and the National Institutes of Health (NIH). Participants do not become employees of NIH, DOE, ORISE, nor ORAU, and there are no employment-related benefits. Qualifications The qualified candidate must be 18 years or older at the time of application and should have received a Master's or Doctoral degree in one of the relevant fields. The degree must have been received within the last five years of the appointment start date. Current graduate students who are nearing degree completion may apply but must have completed their degrees by the start of the fellowship. Citizenship Requirements: This opportunity is available to U.S. citizens, Lawful Permanent Residents (LPR), and foreign nationals. Non-U.S. citizen applicants should refer to the Guidelines for Non-U.S. Citizens Details page for information about the valid immigration statuses that are acceptable for program participation. A Completed Application Consists Of • A complete Zintellect profile. • A program specific application submitted in Zintellect. • Transcript(s) – Submit a copy of your most recent official transcript. For this opportunity, an unofficial transcript or copy of the student academic record printed by the applicant or by academic advisors from internal institution systems may be submitted to complete the application requirement, if you do not have a copy of your official transcript at the time of application. The transcript or academic record must include the name of the academic institution, name of the student, courses completed/in progress, grades and degree expected/awarded. A copy of your official transcript and/or letter showing proof of your degree may be required prior to starting the appointment. All transcripts must be in English or include an official English translation. • A current resume/CV, including academic history, employment history, relevant experiences, and publication list. • One Recommendation - Applicants are required to provide contact information for at least one recommendation in order to submit the application, but two are recommended. You are encouraged to request a recommendation from professionals who can speak to your abilities and potential for success, as well as your scientific capabilities and personal characteristics. Recommendation requests must be sent through the Zintellect application system. Recommenders will be asked to complete a recommendation in Zintellect. Recommendations submitted via email will not be accepted. Recommendations must be submitted before your application can be reviewed. All documents submitted must be in English or include an official English translation. All social security numbers, student identification numbers, and/or dates of birth should be removed (blanked out or blackened out, made illegible, etc.) prior to uploading into the application system. If you have questions, contact us at NIHprograms@orau.org. Please include the reference code NIH-DPCPSI-CAIO-AIPolicy-2026 for this opportunity in your email. Connect with ORISE...on the GO! Download the new ORISE GO mobile app in the Apple App Store or Google Play Store to help you stay engaged, connected, and informed during your ORISE experience and beyond! Stipend $75,000.00 – $88,000.00 Yearly Point of Contact Daphne Eligibility Requirements">3 ) • Degree: Master's Degree or Doctoral Degree received within the last 60 months or currently pursuing. • Discipline(s): • Computer, Information, and Data Sciences (