PhD Research Intern (Measurement and Evaluation)

Abridge
NYC OfficePosted 9 March 2026

Tech Stack

Job Description

PhD Research Intern (Measurement and Evaluation) ABOUT ABRIDGE Abridge was founded in 2018 with the mission of powering deeper understanding in healthcare. Our AI-powered platform was purpose-built for medical conversations, improving clinical documentation efficiencies while enabling clinicians to focus on what matters most—their patients. Our enterprise-grade technology transforms patient-clinician conversations into structured clinical notes in real-time, with deep EMR integrations. Powered by Linked Evidence and our purpose-built, auditable AI, we are the only company that maps AI-generated summaries to ground truth, helping providers quickly trust and verify the output. As pioneers in generative AI for healthcare, we are setting the industry standards for the responsible deployment of AI across health systems. We are a growing team of practicing MDs, AI scientists, PhDs, creatives, technologists, and engineers working together to empower people and make care make more sense. We have offices located in the Mission District in San Francisco, the SoHo neighborhood of New York, and East Liberty in Pittsburgh. THE ROLE We’re looking for research interns to join Abridge’s Strategic Research team for a 12 week program in Summer 2026. In this role, you will work with the Head of Strategic Research on developing and conducting high-impact evaluations of Abridge models and products. As a member of a cross-functional team you will have deep engagements with both the Commercial and Builder sides of our organization. You will gain unique experience conducting research in a startup environment. By bringing methodological rigour on a startup tempo you will have the opportunity to make a meaningful impact on products that directly affect provider wellness and patient outcomes. The Strategic Research team at Abridge has two primary functions: (i) designing and conducting rigorous research studies investigating the impact of ambient AI as an intervention https://pubmed.ncbi.nlm.nih.gov/39775871/ in partnership with collaborating health systems; and (ii) supporting external research efforts that leverage Abridge data. In addition to driving and supporting empirical studies of the impact of ambient AI-enabled technologies, the team works closely with our Science and Engineering teams on core model evaluation. WHAT YOU’LL DO - Design and conduct evaluations of Abridge models and products - Develop a strong user-centric and patient-centric mindset, grounding the research in empathy for the real world experience of providers and patients - Collaborate across our cross-functional product teams to ensure the research is deeply informed by current practices and our product roadmap - Write technical reports and give presentations to internal stakeholders - Receive mentorship from the Head of Strategic Research WHAT YOU’LL BRING - Currently pursuing a PhD in statistics, computer science, economics, information systems, health informatics, or a related field. - Strong research track record in evaluation and measurement, as evidenced by research publications, coursework, and prior work experience. - Demonstrated ability to conduct empirical evaluations using observational or experimental data grounded in a rigorous quantitative or mixed-methods approach. - A curious, adaptable, and proactive mindset, with a desire to learn and grow in a fast-paced startup environment. - Passion for and understanding of Abridge’s mission. ELIGIBILITY - This internship opportunity is currently only open to PhD students enrolled at a US academic institution whose expected graduation date is no sooner than December 2026. WHY WORK AT ABRIDGE? At Abridge, we’re transforming healthcare delivery experiences with generative AI, enabling clinicians and patients to connect in deeper, more meaningful ways. Our mission is clear: to power deeper understanding in healthcare. We’re driving real, lasting change, with millions of medical conversations processed e ... (truncated, view full listing at source)
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