Using Machine Learning to Develop Novel Drug Delivery Systems

Machine learning has revolutionised numerous fields from self-driving technologies to aeronautics and drug discovery, yet its impact remains under-explored in the domain of drug formulation development – an area marked by extensive resource and labour investment. This project aims to harness machine learning to create sophisticated models that can fast-track and fine-tune the development of ground-breaking drug delivery systems.

The project will explore the potential benefits of machine learning in refining the formulation development process and elevating advanced development techniques like additive manufacturing. The selected applicant will receive extensive training across the entire project spectrum, focusing on how machine learning can effectively utilise laboratory results to influence future breakthroughs.

The project will be based at University College London (UCL), a top 10 University in the 2024 QS World Rankings, within the vibrant and welcoming School of Pharmacy. Upon starting, the PhD candidate will join a world-renowned, highly-cited research group, supervised by Professor Abdul W. Basit. The group has multiple decades of academic and commercial experience and a track record of successful spin-outs. During their project, the PhD researcher will have access to gold-standard facilities and resources, with strong mentorship, support, and frequent career development opportunities. The projects will also be in collaboration with broad multidisciplinary teams including medical doctors, clinical hospital pharmacists, engineers and data scientists. 

Applications

The ideal candidate should have (or expect to achieve) a bachelor’s degree or relevant master’s qualification in Pharmacy, Engineering, Computer Science or a related discipline. Prior lab experience and Data Science knowledge will be valued.  It is also desirable to be proficient in Python, with experience in data acquisition. A good level of spoken and written English is essential. Applications are welcomed from both UK and overseas candidates. To apply, please send a CV and cover letter to [email protected].