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The fast-moving consumer goods industry is worth over £4 trillion annually and includes a wide range of essential goods such as food and beverages, personal care products, and household items. Despite this industry's crucial role in society, it still encounters significant production scale-up issues and challenges related to batch-to-batch inconsistencies, usually associated with mixing operations. Moreover, there are constant changes to product formulations every year driven by rapidly evolving consumer needs. Mixing equipment needs to be robustly designed to ensure that new products can be produced at the same or higher capacity in existing manufacturing plants across the globe.
In this project, we will characterise rotor-stator mixers as an efficient technology for robust manufacturing processes of formulated liquids in the personal care and food industries. Rotor-stator mixers consist of a rotor, which typically has blades or teeth attached, and a stationary stator with slots or grooves. The rotor rotates at high speeds within the stator, creating a shearing and mixing action as the product passes through the narrow gap between the rotor and stator. This results in intense turbulence and high shear forces, effectively dispersing, emulsifying, and blending the components of the mixture. Rotor-stator mixers have been proven highly efficient and versatile, capable of handling a wide range of fluid viscosities and producing consistent and uniform blends. They are used for various processes such as homogenisation, emulsification, dispersion, dissolution, and particle size reduction.
The objectives entail studying the flow dynamics and power characteristics of these devices across a wide range of liquid rheological properties (e.g., dense emulsions and highly concentrated surfactant solutions). For this, we will use a combination of Machine Learning and experimental measurements to assess pumping capacity and power dissipation for different mixer geometries and operational conditions. This will be done across different equipment scales (from lab to fully industrial) to deliver design and scale-up rules for a wide range of products, which are invaluable to the industry. The project will use the full range of high-shear mixing equipment existing in the James Chadwick Building of the Department of Chemical Engineering. We are seeking a candidate who is highly motivated to conduct experimental work and utilise machine-learning-based regression tools for processing experimental data.
The project is partially funded by Unilever, which is one of the world's largest consumer goods companies. Unilever owns several well-known brands such as Dove, Knorr, Rexona/Sure, Domestos and Hellmann's. The project will involve strong engagement with the Modelling & Analytics for Processing team at Unilever R&D. Through this project, you will gain proficiency in various computational and experimental techniques used to analyse mixing equipment. These skills are highly valued across a wide range of industries.
Eligibility
Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s (or international equivalent) in Chemical Engineering or other relevant science or engineering-related disciplines.
Before you apply
Applicants are encouraged to contact Dr. Claudio Fonte with a cover letter and a copy of their CV at claudio.fonte@manchester.ac.uk for informal enquiries.
How to apply
Apply online through our website: https://uom.link/pgr-apply-fap
When applying, you’ll need to specify the full name of this project, the name of your supervisor, if you already having funding or if you wish to be considered for available funding through the university, details of your previous study, and names and contact details of two referees.
Your application will not be processed without all of the required documents submitted at the time of application, and we cannot accept responsibility for late or missed deadlines. Incomplete applications will not be considered.
After you have applied you will be asked to upload the following supporting documents:
If you have any questions about making an application, please contact our admissions team by emailing FSE.doctoralacademy.admissions@manchester.ac.uk.
Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact.
We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status.
We also support applications from those returning from a career break or other roles. We consider offering flexible study arrangements (including part-time: 50%, 60% or 80%, depending on the project/funder).
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This 3.5 year PhD project is fully and covers the home tuition fees and a tax free stipend equivalent to the current standard UKRI rate (£20,780 for 2025/26 as reference). EU nationals with settled or pre-settled status can also apply but their application eligibility will be determined on a case-by-case basis. The project must start in September 2025.
Outstanding international candidates are also encouraged to apply, but funding to cover international tuition fees will be determined on a case-by-case basis.
The project must start in September 2025. We are accepting applications until the position is filled.
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