About the Project

This project pioneers formulation design by integrating statistical optimisation tools with advanced molecular-scale simulations and industrial wet-chemistry validation. It will identify optimal detergent compositions from vast molecular design spaces, reveal how molecular chemistry drives performance, and accelerate the discovery of smarter, greener ingredients.

Predicting optimal compositions in home-care products is a major challenge, given the vast design space of often high-value ingredients. In detergents, this requires understanding the complex aqueous chemistry of small molecular components (e.g., fragrance molecules) and how they interact with fibrous materials. Exploring this empirically for the thousands of components available to formulation design would be resource-intensive and impractical. This motivates the PhD project, which will exploit a combined data science–molecular simulation approach, cross-validated with wet chemistry, to optimise existing formulation products and, when combined with state-of-the-art cheminformatics approaches, design new ingredients for sustainable product innovation.

You will employ Bayesian optimisation to systematically reduce large catalogues of potential formulation ingredients based on key descriptors derived from existing data. For the selected subset, enhanced-sampling molecular dynamics approaches will be used to determine mechanisms and rates for the reversible binding of molecules to fibrous surfaces in wet and dry conditions—the key indicators of ingredient performance. The simulations will reveal how molecular topology and chemistry control penetration of the surfactant-rich interfacial layer at fibres during washing, and subsequent molecule release in air.

By integrating these molecular insights with Bayesian inference and cheminformatics, the computational tools developed in this project will enable the efficient selection and prediction of new formulation ingredients for direct evaluation in wet chemistry experiments carried out by industry partners. As such, we are seeking a highly motivated candidate with interests in molecular modelling, digital design for real-world problems, and combining advanced tools in data science with complex molecular-scale problems.

The project will be supervised by Dr Aaron Finney and Prof Simon Maskell from the School of Engineering at the University of Liverpool, and Dr Martin Crossman and Mr Tinto Alencherry from Unilever. The supervisory team brings complementary expertise spanning molecular simulation, Bayesian methods, interfacial science and cheminformatics, providing the full range of skills required to guide the research. Supported by Unilever, this PhD offers close collaboration with industrial R&D teams, linking predictive computational models to sustainable and efficient product innovation.

This project is expected to start in October 2026 and 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 largest industry-academia colocation in UK physical science. The successful candidate will benefit from training in robotic, digital, chemical and physical thinking, which they will apply in their domain-specific research in materials design, discovery and processing. PhD training has been developed with 35 industrial partners and is designed to generate flexible, employable, enterprising researchers who can communicate across domains.

We strongly encourage candidates to get in touch with the supervisory team to get a better idea of the project before making a formal application online. Any informal enquiries about the project can be directed to Aaron.Finney@liverpool.ac.uk. Review our CDT guide on How to Apply carefully as it may differ from a standard application process.

Finally, register and apply online indicating the subject area as Materials Engineering. You'll receive an email acknowledgment once you've submitted your application. We'll be in touch with further details about what happens next.

We will close the application once a suitable candidate is found hence early application is advised. We will interview on a rolling basis and fill the position on a first come, first served principle.

We want all our Staff and Students to feel that Liverpool is an inclusive and welcoming environment that actively celebrates and encourages diversity. We are committed to working with students to make all reasonable project adaptations including supporting those with caring responsibilities, disabilities or other personal circumstances.

Funding Notes

The EPSRC DAMC CDT Studentship will cover full home tuition fees and a maintenance grant for 4 years starting at the UKRI minimum (for the 2025-26 academic year this was £5,006 pa tuition fees and £20,780 pa maintenance grant; rates for 2026-27 academic year TBC). The Studentship also comes with a Research Training Support Grant to fund consumables, conference attendance, etc.

Studentships are available to any prospective student wishing to apply including both home and international students. While EPSRC funding will not cover international fees, a limited number of scholarships to meet the fee difference will be available to support outstanding international students.

If you have a disability you may be entitled to a Disabled Students’ Allowance on top of your studentship to help cover the costs of any additional support that a person studying for a doctorate might need as a result.