PhD Studentship in Multiscale Optimisation of Aperiodic Lattice Metamaterials
Develop next-generation metamaterials with spatially programmable properties using computational optimisation and machine learning.
Best for:Best for candidates with a strong background in engineering, materials science, or computational modelling, passionate about interdisciplinary research at the forefront of metamaterials and additive manufacturing.
Overview
This three-and-a-half-year PhD studentship at The University of Manchester focuses on advancing the design of aperiodic lattice metamaterials. The project integrates computational mechanics, machine learning, and additive manufacturing to create lightweight, high-performance materials with tailored mechanical and thermal properties. By leveraging aperiodic order—inspired by quasiperiodic tilings—the research aims to surpass conventional periodic design frameworks, enabling superior performance under complex loading conditions. The successful candidate will contribute to cutting-edge research at the intersection of structural optimisation, materials science, and artificial intelligence, with potential applications in aerospace, energy, and biomedical engineering.
What you'll do
- Develop multiscale optimisation tools for aperiodic lattice metamaterials using physics-based modelling and machine learning.
- Explore vast design spaces defined by microarchitectures based on aperiodic order to enhance material performance.
- Integrate computational mechanics with data-driven surrogate modelling to enable efficient design exploration.
- Collaborate with advanced manufacturing techniques to prototype and test spatially programmable materials.
- Contribute to establishing new principles for designing materials with tailored mechanical and thermal properties.
- Publish research findings in high-impact academic journals and present at international conferences.
- Engage in interdisciplinary research at the intersection of structural optimisation, materials science, and artificial intelligence.
Requirements
Degree required: A minimum of a 2.1 honours degree or a master’s degree (or international equivalent) in a relevant science or engineering discipline (e.g., Mechanical Engineering, Materials Science, Computational Modelling, or related fields).
Degree offered: PhD
Language: English; proficiency sufficient for academic research and publication.
Instruction: English
- Strong background in computational modelling or materials science.
- Experience with physics-based modelling or machine learning techniques.
- Familiarity with additive manufacturing processes.
- Proficient in programming languages such as Python, MATLAB, or similar.
- Ability to conduct independent research and publish findings.
- Open to UK-based students only.
- Applicants must have, or expect to achieve, at least a 2.1 honours degree or a master’s degree.
Funding & terms
How to apply
Deadline: 2027-01-06
Interested applicants should contact Dr Chikwesiri Imediegwu via email at chikwesiri.imediegwu@manchester.ac.uk. The application should include details of your current level of study, academic background, relevant experience, and a paragraph explaining your motivation for pursuing this PhD project. Follow the university’s PhD application process via the provided link.
- CV
- Academic transcripts (BSc and MSc, if applicable)
- Motivation letter or paragraph explaining interest in the project
- Proof of eligibility (e.g., confirmation of current or expected degree classification)
Contact
Chikwesiri Imediegwu· Supervisor
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