PhD Research Studentships

Experimental / Numerical /Theoretical Study in Solid Mechanics

Supervisor: Tao LIU
Apply by:28 January 2026
Start in:September (Semester 1)

Description

The Research Group

The research objectives of Dr Tao Liu’s group are twofold: firstly, to gain new insights and understanding in the field of the Mechanics of Materials, and secondly, to apply these principles to develop innovative solutions for emerging engineering challenges. The group’s research spans several key areas, including: (1) experimental and theoretical studies on damage and fracture of engineering materials under both static and dynamic loads (e.g., impact and shock), (2) modelling multiphysics behaviours of materials, (3) design optimization of engineering structures and materials, and (4) mechanics of wet adhesion and soft matter. They have substantial experience in developing custom test rigs, such as high-speed impact test setups and traction force microscopy (TFM) systems, as well as in developing specialized numerical simulation frameworks and computational tools. The group has extensive experience leading major research projects. Its research has been funded by DSTL, EPSRC, Innovate UK, Royal Society, Leverhulme Trust, European Union Horizon 2020 and international industry, with a total value of funding around £ 2.5 M. Over the past few years, PhD graduates from Dr. Liu's group have secured prestigious academic positions at various institutions, including Tsinghua University, the University of Manchester, and Huazhong University of Science and Technology, and have also pursued successful industry careers at companies such as D J Goode, TurboMachinery, and Arup.

Description of the PhD project

This PhD opportunity offers a unique oppotunity to investigate engineering challenges in solid mechanics using advanced experimental, numerical, and theoretical methods. There are following two research directions

  • Experimental mechanics

This PhD research advances the frontiers of experimental mechanics through high-resolution Digital Image Correlation (DIC) techniques to investigate complex multiphysics phenomena across three critical domains:

  1. Soft Matter: Including hydrogels, cells, and biological tissues
  2. Advanced Materials: e.g., battery components and composite materials
  3. Natural Systems: e.g. rock mechanics, volcano eruption.

Building on our group's pioneering work in DIC-based Traction Force Microscopy [1], which successfully quantifies deformation and forces at biomaterial-substrate interfaces, this project aims to enhance measurement precision through machine learning integration. The research will specifically focus on achieving high-fidelity, full-field measurements of interface dynamics, including:

  • Friction mechanisms
  • Adhesion properties
  • Suction phenomena

This novel approach combines advanced imaging techniques with AI-driven analysis to provide unprecedented insights into material interface behaviours.

  • High fidelity numerical and theoretical modelling on multiphysics behaviours of engineering materials and structures

Numerical and theoretical modelling is the key step to strengthen our understanding on experiment measurement and provide predictive models for design optimisation purpose. Our research group has developed sophisticated computational frameworks that capture complex multiphysics phenomena in engineering materials and structures. Our modelling portfolio includes:

  • Finite element simulations on failure of metallic and composite materials such phase field modelling on fractures [2], visco-plasticity modelling on creep-plastic behaviours of metals [3], and fibre composites under high-velocity impact [4,5]
  • Discrete element simulations for granular mechanics [6]
  • Coupled multiphysics simulations integrating diffusion and stress fields for self-healing cellular materials [7]
  • Advanced bio-chemo-mechanical frameworks for cytocontractility [8]

We especially welcome applicants with applied mathematics backgrounds. The PhD project can explore in the following areas

  • Machine learning based novel algorithms for solving partial differential equations (PDEs) for a multiphysics event such as batter degradation.
  • Modelling failure of fibre reinforced composites and metals working under hydrogen or helium environment.
  • Network theory inspired structural mechanics – (1) creating efficient load distribution pathways in complex structures to maximise material efficiency; (2) applying graph theory to predict failure patterns; (3) complex network analysis for structural resilience.
  • Bio-chemo-mechanical modelling on tissue fracture.

References

[1] Pang, Y., Sun, W. and Liu, T., 2024. Quasi-static responses of marine mussel plaques detached from deformable wet substrates under directional tensions. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[2] Ragab, R., Sun, W., Li, M. and Liu, T., 2024. Phase-field finite element modelling of creep crack growth in martensitic steels. Engineering Fracture Mechanics, 310, p.110491.

[3] Ragab, R., Liu, T., Li, M. and Sun, W., 2022. Membrane stretching based creep damage analytical solutions for thin disc small punch problem. Journal of the Mechanics and Physics of Solids, 165, p.104928.

[4] Zhang, Y., Liu, T. and Tizani, W., 2018. Experimental and numerical analysis of dynamic compressive response of Nomex honeycombs. Composites Part B: Engineering, 148, pp.27-39.

[5] Turner, P., Liu, T., Zeng, X. and Brown, K., 2018. Three-dimensional woven carbon fibre polymer composite beams and plates under ballistic impact. Composite Structures, 185, pp.483-495.

[6] Liu, T., Fleck, N.A., Wadley, H.N.G. and Deshpande, V.S., 2013. The impact of sand slugs against beams and plates: Coupled discrete particle/finite element simulations. Journal of the Mechanics and Physics of Solids, 61(8), pp.1798-1821.

[7] Cao, S. and Liu, T., 2021. Compressive response of self-healing polymer foams containing bilayered capsules: Coupled healing agents diffusion and stress simulations. Journal of the Mechanics and Physics of Solids, 149, p.104314.

[8] Liu, T., 2014. A constitutive model for cytoskeletal contractility of smooth muscle cells. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 470(2164), p.20130771.

Funding

Funded by: China Scholarship Council
Candidate will need to secure a CSC scholarship.
Under the scheme, Queen Mary will provide scholarships to cover all tuition fees, whilst the CSC will provide living expenses and one return flight ticket to successful applicants.

Eligibility

  • The minimum requirement for this studentship opportunity is a good honours degree (minimum 2(i) honours or equivalent) or MSc/MRes in a relevant discipline.
  • If English is not your first language, you will require a valid English certificate equivalent to IELTS 6.5+ overall with a minimum score of minimum score of 6.0 in each of Writing, Listening, Reading and Speaking).
  • Candidates are expected to start in September (Semester 1).

Contact

For informal enquiries about this opportunity, please contact Tao LIU.

Apply

Start an application for this studentship and for entry onto the PhD Materials Science full-time programme (Semester 1 / September start):

Apply Now »

Please be sure to quote the reference "SEMS-PHD-625" to associate your application with this studentship opportunity.

SEMS Research Centre:
Intelligent Transport
Keywords:Biophysics, Aerospace Engineering, Mechanical Engineering, Materials Science - Other, Mathematical Modelling, Biomechanics, Experimental Physics