Junior Clinical Research Doctor

About nference Labs, Bangalore nference Labs Bangalore is the India hub of nFerence, a global leader in computational biomedicine. Our Bangalore team works closely with world-class scientists, clinicians, and AI researchers to build cutting-edge biomedical intelligence platforms. The team plays a key role in advancing solutions that triangulate data from biomedical literature, molecular datasets, and real-world clinical information. The Bangalore office provides a fast-paced tech and research environment, encourages innovation, and offers opportunities to collaborate on groundbreaking biomedical AI initiatives. Requirements* MBBS from a reputed medical institution in India; candidates with other undergraduate degrees need not apply.

• Strong understanding of clinical medicine and patient care.
• Ability to search, review, and understand scientific literature including PubMed articles, medical journals, and research publications.
• Basic computer literacy including good familiarity with office suites.
• Basic familiarity with prompt engineering for Large Language Models such as ChatGPT, Gemini, etc.
• Elementary knowledge of biostatistics (preferred).
• Understanding of Electronic Health Record (EHR) data within the US healthcare system (preferred).
• Prior experience working in a technology or corporate environment (preferred).

Job Description* Clinical Data Harmonisation: Manually validate the process of transforming data optimised for storage into easily computable data for research.

• Reviewing patient notes in Electronic Health Records when required.
• Working in close proximity with the AI team in developing high-quality software to interpret Electronic Health Records.
• Tagging datasets with high-level accuracy for the development of artificial intelligence models.

Benefits* Opportunity to become a permanent part of the “Google of Biomedicine” as recognised by the Washington Post.

• Work with some of the brightest minds in the world solving impactful real-world problems through AI, Machine Learning, analytics, and insights derived from both structured and unstructured biomedical data.