PhD Studentship: Calibration Methodologies for Industrial/Geophysics Granular Materials
The University of Manchester
This 3.5-year PhD project is fully funded and home students are eligible to apply. The successful candidate will receive an annual tax-free stipend set at the UKRI rate (£21,805 for 2026/27) and tuition fees will be paid. We expect the stipend to increase each year. The start date is October 2026. We recommend that you apply early as the advert may be removed before the deadline. This PhD project addresses the "calibration problem" in particulate continuum models and particle simulations. Specifically, it focuse...
This 3.5-year PhD project is fully funded and home students are eligible to apply. The successful candidate will receive an annual tax-free stipend set at the UKRI rate (£21,805 for 2026/27) and tuition fees will be paid. We expect the stipend to increase each year. The start date is October 2026. We recommend that you apply early as the advert may be removed before the deadline. This PhD project addresses the "calibration problem" in particulate continuum models and particle simulations. Specifically, it focuse...
Opportunity details
This 3.5-year PhD project is fully funded and home students are eligible to apply. The successful candidate will receive an annual tax-free stipend set at the UKRI rate (£21,805 for 2026/27) and tuition fees will be paid. We expect the stipend to increase each year. The start date is October 2026. We recommend that you apply early as the advert may be removed before the deadline. This PhD project addresses the "calibration problem" in particulate continuum models and particle simulations. Specifically, it focuses on developing robust methodologies for selecting and parameterising contact models, a crucial but challenging task due to the lack of standardised measurement techniques. The research will explore and refine "indirect" or "bulk" calibration methods, using characterisation machines to match simulation results with experimental data. This project will integrate advanced AI techniques, including machine learning for parameter optimisation (e.g., Bayesian optimisation, reinforcement learning), AI-driven model selection, and deep learning for data analysis and feature extraction from characterisation data. Surrogate modelling will be employed to reduce computational costs, and AI-based uncertainty quantification will enhance the reliability of calibrated parameters. Overcoming challenges like dimensionless indices, varying machine types across disciplines, and multi-parameter dependencies, the project aims to establish improved, AI-enhanced calibration strategies for diverse industrial and geophysical materials. Ultimately, it seeks to determine the optimal, AI-informed approach for selecting and calibrating discrete particle models for specific materials. Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s (or international...
Eligibility
This 3.5-year PhD project is fully funded and home students are eligible to apply. The successful candidate will receive an annual tax-free stipend set at the UKRI rate (£21,805 for 2026/27) and tuition fees will be paid. 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. 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.
Requirements
This 3.5-year PhD project is fully funded and home students are eligible to apply. The successful candidate will receive an annual tax-free stipend set at the UKRI rate (£21,805 for 2026/27) and tuition fees will be paid. 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. 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.
Funding and benefits
Funding eligibility: UK Students. Funding amount: £21,805 annual tax-free stipend set at the UKRI rate and tuition fees will be paid.
How to apply
This 3.5-year PhD project is fully funded and home students are eligible to apply. We recommend that you apply early as the advert may be removed before the deadline. Specifically, it focuses on developing robust methodologies for selecting and parameterising contact models, a crucial but challenging task due to the lack of standardised measurement techniques. To apply please contact Dr Anthony Thornton - Anthony.Thornton@manchester.ac.uk.
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Recorded source check: July 14, 2026. A stored check date does not guarantee that every field is complete or still current. Compare the provider, eligibility, funding and deadline with the live official call before applying.
Benefits
Funding eligibility: UK Students. Funding amount: £21,805 annual tax-free stipend set at the UKRI rate and tuition fees will be paid.
Eligibility summary
Requirements
This 3.5-year PhD project is fully funded and home students are eligible to apply. The successful candidate will receive an annual tax-free stipend set at the UKRI rate (£21,805 for 2026/27) and tuition fees will be paid. 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. 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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