Undergraduate Research Trainee — AI & Medtech (Pre-Med, Summer 2026)
About TurnKey AI Practice. TurnKey AI Practice is an early-stage healthcare technology company building a HIPAA-compliant, musculoskeletal-focused AI platform for independent orthopaedic and physical therapy practices. We are physician-founded and operate at the intersection of clinical care, research, and applied AI.
About the Program. This is an unpaid, full-time summer educational research experience for a pre-medical undergraduate student. The trainee will contribute to a funded research program supported by the American Shoulder and Elbow Surgeons (ASES) Foundation National Shoulder and Elbow Week (NSEW) Grant. The project: developing the research-methodology foundation for an AI-agentic operating system that automates clinical research workflows in orthopaedics.
Leadership. Principal Investigator: Nathan Boes, MD. Senior Investigator and day-to-day mentor: Justin T. Smith, MD (fellowship-trained orthopaedic sports medicine surgeon; Assistant Professor, Wake Forest University School of Medicine; Founder and CEO, TurnKey AI Practice). Technical mentor: Chris Conlan (CTO). Program coordinator: Sruthi Sudarsan.
What you will do. Lead a PRISMA-ScR scoping review on AI-agentic systems for clinical research workflows in orthopaedics. Register the protocol on the Open Science Framework. Execute database searches in PubMed, Embase, Scopus, IEEE Xplore, ACM Digital Library, and the Cochrane Library, with medical-library support from Wake Forest's Coy C. Carpenter Library. Conduct dual-reviewer title and abstract screening, full-text review, andstructured data extraction. Synthesize findings into a publication-ready manuscript (target journals: JSES International, Cureus, JMIR Medical Informatics). Build a catalog of validated patient-reported outcome measures for shoulder, elbow, and knee pathology. Contribute to a draft validation plan for the research-agent platform.
What you will gain. ICMJE-qualifying authorship on one (committed) or two (stretch) peer-reviewed manuscripts. Direct mentorship from a practicing orthopaedic surgeon-founder and engineering leadership. Letter of recommendation for medical school applications upon successful completion. Structured curriculum covering research methodology, clinical research operations, AI in medicine, and scientific writing. Exposure to the operations of a funded AI healthcare startup, including clinical practice, product development, and grant reporting. Networking in orthopaedic professional societies and the local AI and medtech
community.
Working arrangement. 40 hours per week. Three days in-person at BNA Rock Hill, two days remote. Weeks 1 and 8 fully on-site for onboarding and wrap-up. Standard hours 8:30 AM to 5:00 PM Eastern with flexibility. The trainee does not access protected health information; all datasets are de-identified or synthetic. Required training in Week 1 includes HIPAA awareness, information security, acceptable-use policy, and CITI-equivalent research ethics.
QUALIFICATIONS / MINIMUM REQUIREMENTS
Undergraduate student in good standing at an accredited U.S. institution, preferably a rising junior or senior.
Pre-medical track with documented trajectory toward medical school (coursework, clinical exposure, or shadowing).
Academic credit obtainable through the home institution for the June 1 to July 24, 2026 term (stated intent required at application; written confirmation required before Day 1).
Coursework or demonstrated competency in at least one of: molecular/cell biology, physiology, biostatistics, or health sciences.
Documented interest in artificial intelligence, healthcare technology, or digital health.
Strong scientific writing and reading comprehension in English.
Ability to commit 40 hours per week for 8 consecutive weeks.
Ability to be on-site in Rock Hill, SC during Weeks 1 (June 1–5) and 8 (July 20–24)
PREFERRED QUALIFICATIONS
Prior research experience (bench, clinical, literature review, or public health).
Basic Python literacy (pandas, Jupyter) or willingness to ramp quickly.
Familiarity with PubMed, Embase, Cochrane, or Scopus search syntax.
Power-user familiarity with large language models such as Claude or ChatGPT, including prompting fundamentals.
Interest in orthopaedics, sports medicine, physical therapy, or musculoskeletal care.
APPLICATION INSTRUCTIONS
Submit the following through Handshake:
1. Current CV or résumé.
2. Unofficial transcript from the home institution.
3. One-page personal statement (PDF, single-spaced, 11-point minimum) responding to: "Describe why you are interested in the intersection of AI, medicine, and orthopaedic research, and what you expect to contribute in 8 weeks."
4. Name and contact information for one academic or research reference. A full letter of recommendation will be requested only from finalists.
5. Brief statement confirming that academic credit is obtainable at your home institution for this term (formal written confirmation required before the start date).
Applicants advancing past the initial review will be invited to complete a short supplemental writing exercise (two short paragraphs; sent by email; 72-hour turnaround) before interviews. Two interview rounds follow — Round 1 (20 minutes, program coordinator) and Round 2 (45 minutes, Dr. Smith and Dr. Boes). Decisions communicated within 48 hours of Round 2.
Questions: contact Sruthi Sudarsan at sruthisudarsan@turnkeyaipractice.io