About the Project
This PhD project focuses on the simulation and modelling of wet and cohesive powders, which play a crucial role in industries such as pharmaceuticals, food processing, and additive manufacturing. Despite their importance, the complex behaviour of these materials — driven by capillary forces, adhesion, and particle cohesion — remains challenging to predict and control.
The research will begin with detailed particle-based simulations to capture the micro-mechanical interactions in wet and cohesive systems, using open-source software such as MercuryDPM. These high-fidelity simulations will provide the foundation for understanding key phenomena like agglomeration, flow behaviour, and mixing efficiency.
Building on these insights, the project will then develop reduced-order models (ROMs) to describe the system's behaviour in a more computationally efficient manner, using tools like pyMOR. These ROMs will balance accuracy and speed, enabling faster predictions for large-scale processes. Finally, the ROM will be solved in oomph-lib and advanced optimisation techniques will be applied to design and improve the quality of mixing.
This work offers the opportunity to combine fundamental physics, numerical modelling, and data-driven approaches to tackle industrially relevant challenges. It would suit a candidate with a strong background in applied mathematics, physics, or engineering and an interest in computational modelling and optimisation and industrial application.
This project is expected to start in September 2027.
Before you apply: We strongly recommend that you contact the supervisors for this project before you apply.
How to apply: To be considered for this project you must complete a formal application through our online application portal. If you already have an applicant account this link will directly open an application for PhD School of Natural Sciences Scholarships. If you don't already have an applicant account, please follow the instructions here.
When applying, please specify the full title and supervisor/s of the project, details of your previous study, and names and contact details of two referees. You must also upload a Supporting Statement describing your motivation to apply to the project, your CV and transcripts of awarded and in-progress university qualifications. Please note late or incomplete applications will not be considered.
Equality, diversity and inclusion are fundamental to the success of The University of Manchester and central to all our activities. A diverse research community strengthens creativity, productivity and quality, while increasing the societal and economic impact of our work. We welcome applicants from all career paths, backgrounds and sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation or transgender status.
We welcome applications from candidates returning to study after a career break or experience in other roles. Flexible study arrangements may be available, including part-time study at 50%, 60% or 80%, subject to the requirements of the project and funder.
Eligibility: The standard academic entry requirement for this PhD is an upper second-class (2:1) honours degree (or international equivalent) in Mathematics, Computer Science or Engineering OR any upper-second class (2:1) honours degree and a Master's degree at merit (or international equivalent) in Mathematics, Computer Science or Engineering.
This project will remain open until filled.
If your application is submitted by 1st November 2026, you can expect a decision by 18th December 2026.
If your application is submitted by 15th January 2027, you can expect a decision by 30th March 2027.
Self or externally funded students can also be considered for this project.
FSE_SoNS
Funding Notes
Funding covers tuition fees, an annual stipend at the UKRI minimum rate (currently £21,805 per year), and a research training support grant of up to £2,500 per year for the full 3.5-year programme.