[Stipend at UKRI rate; funding covers stipend and likely tuition as per UKRI standards.] This PhD studentship at University College London (UCL) offers an exciting opportunity to develop a machine learning-accelerated NMR platform for the discovery of inhibitors targeting viral RNA polymerases (RNAPs). RNAPs are essential enzymes for viral replication and represent promising targets for antiviral drug development, with relevance to both RNA and large DNA viruses such as African Swine Fever Virus (ASFV). The project addresses the urgent need for novel antiviral therapies and pandemic preparedness by focusing on rapid, structure-guided drug discovery. Supervised by Professor Finn Werner and Dr. Christopher Waudby, the student will join the Werner and Waudby labs, which provide complementary expertise in viral molecular biology, structural biology, and NMR spectroscopy. The research will build on recent advances in recombinant RNAP production, cryo-EM structural elucidation, and fragment-based screening. The core methodology integrates fluorine-based NMR spectroscopy with active learning algorithms and robotic automation to identify and optimise lead compounds. This multidisciplinary approach will serve as a test case for a generalisable platform for antiviral discovery. Key research activities include producing recombinant viral RNAP transcription complexes in insect cells, functionally characterising RNAP activity, screening fragment libraries using NMR, developing an active learning-driven platform for compound selection, and integrating robotic sample preparation and automated data acquisition. The project aims to advance five existing candidate compounds toward lead optimisation and patent readiness. The student will receive comprehensive training in structural biology (including cryo-EM), biochemical assay development, medicinal chemistry, NMR spectroscopy, machine learning, laboratory automation, and high-throughput experimentation. The collaborative environment at UCL, including access to the UCL Automation Network and state-of-the-art facilities, will support both fundamental and translational research outcomes. Applicants should have a background in biochemistry, structural biology, medicinal chemistry, or related disciplines. Experience with NMR, protein expression, or computational methods is advantageous, and a strong interest in antiviral drug discovery and interdisciplinary research is expected. The position is fully funded with a stipend at the UKRI rate, and applications should be submitted via the Centre for Doctoral Training in Engineering Solutions for Antimicrobial Resistance by 12th January 2026. For further details and to apply, visit the application link provided. This studentship offers a unique opportunity to contribute to next-generation antiviral strategies in a world-class research environment.