PhD in dynamic assembly of surfactant & polymer mixtures for next generation green formulations

About the project

About the Project A PhD position in soft matter science and engineering is available for an October 2026 start date (or ASAP thereafter) in the department of Chemical Engineering, in close collaboration with industrial partners. The project will examine the molecular architecture and association of surfactants and polymers in the context of sustainable liquid formulations of academic interest and industrial relevance. You will develop and employ advanced experimental approaches to examine the dynamic assembly and function of surfactant-polymer mixtures to establish design rules for synergy and superior performance in terms of molecular economy, sustainability and ‘cleaning’ efficiency. You will work integrated within an active academic-industrial team developing digital and physical workflows, to support the transition of the Formulations sector towards sustainable innovation, greater agility and robustness. “Formulations” are complex mixtures of multiple components that are generally out of thermodynamic equilibrium, and whose predictive design is inherently challenging. These are ubiquitous in a range of industries, including consumer goods, detergents, pharmaceuticals and foods, representing approximately £180 billion pa in the UK alone and with great potential to grow further. Our project builds upon recent advances in the fields of high-throughput experimentation, artificial intelligence and computer-aided molecular discovery to disrupt and accelerate molecular design of functional polymers, based on sustainability and performance objectives, towards net-zero formulations. The integration of digital and physical workflows offers exceptional potential for the UK Formulations sector to become a world-leader by unlocking superior performance and reaching net zero by multi-objective optimisation. The experimental component of the project will develop and exploit fluidic and data approaches, coupled with advanced fibre-optic dynamic light scattering and imaging, to explore the large parameter and process spaces associated with formulations. We will also exploit recently developed robotic platforms, able to autonomously screen across composition and environmental spaces, with statistical significance. In partnership with Procter & Gamble and BASF, we will translate our findings in the design the design of novel green formulations. Digital workflows, hybrid machine learning methods, and advanced design of experiments will be integrated with the physical experimentation to tackle the complexity of the composition and process space of formulations. Relevant publications: Torquato et al Lab Chip 23, 2540-2552 (2023), Ahmad et al Nano Lett. 25, 2, 740–746 (2025); Mater Horiz 13, 3658 (2025); Tyagi et al JCIS , 670, 540-549 (2024); JCIS 723, 140936 (2026) Applicants should hold a Master’s degree or (equivalent) in Chemical Engineering, Chemistry, Physics (or related discipline). We encourage applications from under-represented groups. The project will last 4 years. Academic knowledge of soft matter science, fluid mechanics, scattering and data analysis, instrument control and automation, and machine learning is desirable. The PhD studentship is open to UK students only. Start date: October 2026 (or ASAP thereafter) The Department of Chemical Engineering at Imperial College London offers an advanced PhD training programme and access to state-of-the-art experimental and computational facilities , unique Automated high-throughput platform suite , the Sargent Centre for Process Systems Engineering and the Sustainable Futures Lab . The Department holds a Silver Athena Swan award, recognising support of women at all stages as well as our commitment to removing barriers to equal progress and achievement. In order to be considered for the Chemical Engineering PhD, you will need to submit your application for admission through the online admissions system . Full details on the application and selection process can be found on our webpages . We encourage all interested applicants to contact Prof Joao Cabral ( j.cabral@ic.ac.uk ) before making an application.

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