Clinical AI / Machine Learning Research Intern

Company Description Instinkt AI helps physicians transform complex patient information into clear, evidence-informed clinical insights at the point of care. The platform synthesizes patient history, symptoms, investigations, and clinical data to surface relevant differential diagnoses, supporting medical evidence, and draft treatment approaches for clinician review. Designed to augment, not replace, clinical judgment, Instinkt enables doctors to reason faster, stay current with medical knowledge, and make more confident decisions. The team works at the intersection of medicine and machine learning, building tools that aim to improve real-world clinical workflows and patient outcomes.
Role Description This full-time, on-site Clinical AI / Machine Learning Research Intern role is based in Bengaluru. The intern will collaborate with clinicians, data scientists, and engineers to design and execute research studies that evaluate and improve Instinkt’s clinical AI models. Day-to-day responsibilities include conducting literature reviews, curating and annotating clinical datasets, helping design experimental protocols, and analyzing model performance against clinical benchmarks. The intern will contribute to documentation, draft internal research reports, and support the translation of research findings into product features. The role involves regular interaction with medical professionals to understand clinical workflows and ensure that AI outputs remain aligned with real-world clinical needs.
Qualifications
Strong foundation in Medicine or clinical sciences, with interest in applying medical knowledge to AI-driven decision support.
Skills in Research and Clinical Research, including study design, data collection, and basic statistical analysis.
Effective Communication skills, with the ability to collaborate across clinical and technical teams and present findings clearly.
Experience or interest in Training activities, such as contributing to model evaluation protocols or helping refine annotation guidelines.
Relevant academic background (e.g., MBBS, MD, MPH, or biomedical/health-related degree; advanced students in these fields are encouraged to apply).
Understanding of basic machine learning concepts and comfort working with structured clinical data; programming skills (e.g., Python) are a plus.
High attention to detail, strong ethical standards for handling sensitive health data, and commitment to patient-centered innovation.
Ability to work on-site in Bengaluru, collaborate in a fast-paced environment, and manage multiple research tasks independently.

Work arrangement
No