GNOSIS builds the verification and accountability layer for AI in healthcare. We are hiring three paid graduate interns through Memorial University's School of Graduate Studies to help build the system that checks whether an AI-generated clinical note is actually true, before it reaches a patient's chart.
Application deadlineSunday, July 26, 2026 · 11:59 p.m.Apply now →
Three open roles · GNOSIS Ethical Intelligence Inc.
Role 01
AI Verification Engineer Intern
Machine Learning · NLP · Evaluation
You will work on the heart of what we do: the engine that reads an AI-generated clinical note and checks every statement against the source of what actually happened, then proves it or flags it.
What you will do
Develop and refine the verification engine: semantic and token matching, negation and scope handling, numeric and dose-mismatch detection, and flagging of unsupported or fabricated statements.
Design evaluation methods and test sets that measure what the engine catches and misses, with precision and recall that hold up to clinical and audit scrutiny.
Work with large language models in a grounded, cited, human-in-the-loop pipeline. No source, no claim.
Who you are
A graduate student in computer science, machine learning, computational linguistics, or a related field.
Comfortable in Python and/or JavaScript, with a working grasp of NLP and LLM evaluation.
You will connect GNOSIS to the systems clinicians actually use, bringing clinical notes and source records in, and pushing verified, signed notes back to the chart.
What you will do
Build and test integrations with electronic medical records and AI scribes using healthcare standards, primarily FHIR (for example DocumentReference).
Map and normalize clinical data (medications, encounters, findings) so a note can be checked against its true source.
Work on the capture-the-source, verify, return-the-signed-note loop, with privacy by design in line with PHIA.
Who you are
A graduate student in health informatics, computer science, biomedical or health data, or a related field.
Interested in FHIR, HL7, health-data interoperability, and clinical workflows.
All three roles are paid graduate internships hosted through Memorial University's School of Graduate Studies Graduate Internship Program. Applications close Sunday, July 26, 2026 at 11:59 p.m.
Apply through the program link below. If you know a strong graduate student, please pass this along.