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 2026 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 project will also be in collaboration with broad multidisciplinary teams including medical doctors, clinical hospital pharmacists, engineers and data scientists.

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 2026 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 project will also be in collaboration with broad multidisciplinary teams including medical doctors, clinical hospital pharmacists, engineers and data scientists.