NIH Artificial Intelligence Market Analysis

Organization National Institutes of Health (NIH) Reference Code NIH-DPCPSI-CAIO-AIMarketAnalysis-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 This postdoctoral research opportunity is currently available within the National Institutes of Health (NIH), Office of the Chief Artificial Intelligence Office (CAIO). As part of the NIH CAIO program, the participant will engage in mentored research focused on establishing an artificial-intelligence-based market analysis solution. The experience focuses on developing innovative AI-driven solutions that reflect the needs, priorities, and perspectives of diverse NIH leadership and scientific communities. What will I be doing? Guided by the Chief Artificial Intelligence Officer at the NIH and the CAIO team, participants will delve into creating advanced pipelines for market analysis and investigating ways to automate these processes using agentic AI systems. The experience provides a hands-on opportunity to design AI workflows that dynamically translate insights from stakeholder personas into adaptive communication and operational frameworks. Participants will have the chance to engage with cutting-edge technologies while examining how AI can drive organizational transformation in a large-scale research enterprise. By the conclusion of this immersive STEM learning experience, participants will have cultivated valuable skills in: • Designing and optimizing AI workflows: Participants will explore how to implement and evaluate agentic AI systems that utilize large language models to generate synthetic personas representing diverse stakeholder groups, such as industry vendors, biotech companies, startups, healthcare providers, and federal agencies. • Building accessible AI tools: Participants will develop strategies for creating scalable artificial intelligence solutions, including intuitive graphical user interfaces, to ensure accessibility for researchers and scientists with minimal coding expertise. • Applying human-centered AI principles: Through hands-on activities, participants will learn methods for integrating AI into organizational and operational contexts, gaining insight into the role of artificial intelligence in driving organizational change and improving workflows. • Connecting AI systems to dynamic databases: Participants will gain experience in integrating large language models with live data sources, employing techniques such as programmatic APIs, model context protocol servers, and other advanced methods to enable seamless data interaction. This STEM-focused learning experience equips participants with cutting-edge skills at the intersection of artificial intelligence, systems design, and organizational innovation. Why should I apply? This STEM learning experience offers the chance to explore NIH's collaborative research programs, learn how to navigate NIH databases and tools for data analysis, and identify metrics and indicators for evaluating program outcomes. Participants will gain insights into comparing the success of various research initiatives and develop recommendations for future programs based on data-driven findings. This unique opportunity provides a pathway to deepen your knowledge of artificial intelligence, organizational dynamics, and STEM innovation—all under the guidance of expert mentors. 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-AIMarketAnalysis-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! Point of Contact Daphne Eligibility Requirements">5 ) • Degree: Master's Degree or Doctoral Degree received within the last 60 months or currently pursuing. • Discipline(s): • Computer, Information, and Data Sciences (