About the Project
Laser Powder Bed Fusion (LPBF) additive manufacturing involves complex multi-physics across disparate length and time scales. Predicting defect formation—such as keyhole porosity, spatter generation, and rough surface topologies—requires capturing both the discrete granular dynamics of powder recoating and the continuum thermal-fluid physics of laser melt pools.
This PhD project aims to bridge these regimes by creating a high-performance, two-way coupled open-source numerical framework. You will combine MercuryDPM (for Discrete Element Method simulation of powder deposition) and laserbeamFoam (an OpenFOAM-based CFD solver with advanced laser ray-tracing and melt pool hydrodynamics) using the open-source preCICE coupling engine.
By establishing an automated, bidirectional feedback loop between the discrete particle bed and the solidified continuum melt track across successive layers, this project will unlock fundamental insights into layer-by-layer defect propagation in metallic 3D printing.
This will be a joint PhD between the Department of Mathematics and Department of Materials at The University of Manchester. The primary focus of the project is on developing and integrating this novel open-source computational tool, with numerical predictions validated against high-resolution X-ray tomographic reconstructions and surface profilometry.
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 Engineering, Computer Science or Mathematics OR any upper-second class (2:1) honours degree and a Master's degree at merit (or international equivalent) in Engineering, Computer Science or Mathematics.
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 for this project covers tuition fees, UKRI minimum annual stipend (currently £21,805/annum) and up to a £2.5k/annum research training support grant for the full duration of the 3.5-year programme.