Simon Maskell

This PhD project at the University of Liverpool, supervised by Dr Aaron Finney and Prof Simon Maskell, focuses on the molecular modelling and data-driven discovery of sustainable home-care products, particularly detergents. The research integrates statistical optimisation tools, advanced molecular-scale simulations, and industrial wet-chemistry validation to identify optimal detergent compositions from vast molecular design spaces. The project aims to reveal how molecular chemistry drives performance and accelerate the discovery of smarter, greener ingredients for home-care applications. Predicting optimal compositions in detergents is a major challenge due to the complex aqueous chemistry of small molecular components and their interactions with fibrous materials. Empirical exploration of thousands of available components is resource-intensive and impractical, motivating a combined data science and molecular simulation approach. The project will employ Bayesian optimisation to systematically reduce large catalogues of potential formulation ingredients based on key descriptors derived from existing data. Enhanced-sampling molecular dynamics will be used to determine mechanisms and rates for the reversible binding of molecules to fibrous surfaces in wet and dry conditions, which are key indicators of ingredient performance. Simulations will provide insights into how molecular topology and chemistry control penetration of surfactant-rich interfacial layers at fibres during washing and subsequent molecule release in air. By integrating these molecular insights with Bayesian inference and cheminformatics, the computational tools developed will enable efficient selection and prediction of new formulation ingredients for direct evaluation in wet chemistry experiments with industry partners, including Unilever. The project is offered under the EPSRC Centre for Doctoral Training in Digital and Automated Materials Chemistry, based in the Materials Innovation Factory at the University of Liverpool. The successful candidate will benefit from training in robotic, digital, chemical, and physical thinking, applied to materials design, discovery, and processing. The CDT training, developed with 35 industrial partners, aims to generate flexible, employable, and enterprising researchers who can communicate across domains. Funding is provided through the EPSRC DAMC CDT Studentship, covering full home tuition fees and a maintenance grant for 4 years (2025-26: £5,006 tuition, £20,780 maintenance; 2026-27 rates TBC). A Research Training Support Grant is included for consumables and conference attendance. Studentships are available to both home and international students, with limited scholarships to cover the fee difference for outstanding international candidates. Disabled Students’ Allowance is available for eligible candidates. Applicants should have a strong academic background in chemistry, chemical engineering, materials science, or related fields, with interests in molecular modelling, digital design, and advanced data science tools. The project starts in October 2026, and applications are accepted until 31st March 2026 or until the position is filled. Early application is advised as interviews are conducted on a rolling basis. For further information or informal enquiries, contact Dr Aaron Finney at [email protected]. Please review the CDT guide on 'How to Apply' as the process may differ from standard applications. Register and apply online, indicating Materials Engineering as the subject area. The University of Liverpool is committed to diversity and inclusion, supporting reasonable project adaptations for students with caring responsibilities, disabilities, or other personal circumstances.