Job Summary

This position is part of an RD team building hybrid quantum-classical frameworks that help LLMs reason more reliably over biomedical literature - extracting structured knowledge and generating testable hypotheses (e. g. , drug-target interactions, drug repurposing candidates, mutation disease associations) with explicit provenance rather than unconstrained generation.

Responsibilities
The role will involve RD focused on:
Quantum-enhanced extraction of knowledge graphs from biomedical literature, applying quantum graph neural networks to identify entities, relationships, and patterns across large corpora of biomedical publications.
Quantum semantic encoding of biomedical text papers, abstracts, and clinical literature to support downstream reasoning at a scale that addresses the rapid growth of unstructured biomedical data.
Hybrid quantum-classical retrieval-augmented reasoning pipelines for literature-grounded hypothesis generation in the medical domain, with explicit evidence provenance linking each generated hypothesis (e. g. , a candidate drug-target interaction) back to its supporting literature.
Evaluation of truthfulness,



hallucination, and calibrated confidence in quantum-augmented biomedical hypothesis generation using automated methods cross-referencing generated drug-target hypotheses against curated interaction databases (DrugBank, ChEMBL, DGIdb) and retrospective temporal-split testing, combined with quantum-derived confidence/uncertainty scoring.
Development of a quantum-enhanced biomedical claim-verification module for scientific literature: automatically classifying each generated claim or hypothesis against retrieved evidence as Supported, Refuted, or Not Enough Information, extending established scientific claim-verification frameworks (e. g. , SciFact- and HealthVer-style benchmarks) with quantum semantic encoding for evidence-claim matching.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Postdoctoral Fellowship Chennai
🏢 Amrita Vishwa Vidyapeetham
📍 Chennai