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We are now recruiting for the 2026 cohort

The Resident Doctor Research Group (RDRG) was established in 2025 to ensure that clinical expertise remains central to the development and evaluation of digital technologies within the NHS. 

Digital innovations are only successful when they reflect the realities of clinical practice. Through the RDRG, Resident Doctors work alongside clinicians, researchers and data scientists to shape the development, evaluation and implementation of artificial intelligence and digital technologies that improve patient care and support healthcare professionals. 

Since its launch, 25 Resident Doctors have been recognised as named authors on high-impact publications. 

Join the RDRG 

Become part of a growing network of clinicians exploring how artificial intelligence, machine learning and digital technologies can improve patient care, support healthcare professionals and transform the NHS. 

No previous experience in artificial intelligence, programming or data science is required - only an interest in improving healthcare through research and innovation. 

What you'll gain 

As a member of the RDRG, you'll have the opportunity to: 

• Contribute to meaningful research with real-world clinical impact. 

• Gain hands-on experience of emerging AI and digital health technologies. 

• Collaborate with clinicians, researchers and data scientists. 

• Develop your academic portfolio through publication and research opportunities. 

• Help shape technologies that are being developed for use within the NHS.

Register your interest 

To join the Resident Doctor Research Group, email your full name to: imperial.icaresde@nhs.net 

Alternatively, complete our online registration form:  

Previous research 

Members of previous RDRG cohorts have contributed to several high-impact research projects, including: 

Real-World Implementation of Large Language Models for Writing Clinical Discharge Summaries Within a Secure Data Environment (JMIR AI, 2026) 

Resident Doctors co-designed the evaluation methodology and provided expert clinical assessment of AI-generated discharge summaries, helping determine whether the technology was safe and clinically acceptable for real-world NHS use. 

URL:   
DOI: 10.2196/88816 

 Large Language Model-Generated Discharge Summaries: A Retrospective Non-Inferiority Study Using Real-World Hospital Data (JAMA Network Open, in review) 

Resident Doctors assessed the safety, accuracy and usability of AI-generated discharge summaries. 

URL: