Qualification Type: | PhD |
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Location: | Manchester |
Funding for: | UK Students, EU Students |
Funding amount: | £19,237 Tax free stipend set at the UKRI rate (£19,237 for 2024/25) and tuition fees will be paid |
Hours: | Full Time |
Placed On: | 10th March 2025 |
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Closes: | 27th June 2025 |
This 3.5 year PhD project is fully funded and home students, and EU students with settled status, are eligible to apply. The successful candidate will received an annual tax free stipend set at the UKRI rate (£19,237 for 2024/25) and tuition fees will be paid. We expect the stipend to increase each year.
Hypothesis and Objectives
Project Description
Lubricants are not simple liquids. The surfactant molecules present in such systems self-assemble into aggregates and these aggregates, in turn, interact with each other to form a wide variety of phases. These structures have a profound effect on a lubricant’s adsorption and rheology, both key factors affecting lubricant efficiency. Because of the complexity of the systems special modelling methods are required to probe this behaviour. This PhD project is aimed at developing a novel methodology based on the use of local density dependent potentials (LDPs).
Specific aims are:
The student will be trained in the use of high-performance computing and in programming. They will also receive a firm grounding in rheology, statistical mechanics and the use of Machine Learning techniques.
Impacts:
Benefits for the student:
Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline.
To apply, please contact the main supervisor; Prof Andrew Masters - andrew.masters@manchester.ac.uk. Please include details of your current level of study, academic background and any relevant experience and include a paragraph about your motivation to study this PhD project.
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