PhD Research Studentships
AI-guided design and fabrication of next-generation soft bioinspired materials
| Supervisor: | Marco PENSALFINI |
| Apply by: | 28 January 2026 |
| Start in: | September (Semester 1) |
Description
Dr. Pensalfini’s group at Queen Mary University of London invites applications for PhD studentships under the CSC–QMUL joint scheme, with envisioned start date in September 2026.
For centuries, scientists and engineers have been looking at Nature as a source of inspiration to conceive and implement material innovations. One notable example are nacre-inspired composites, which offer unprecedented combinations of toughness and stiffness [1]. Only recently the attention has turned to implementing bioinspired design principles in highly deformable materials [2, 3]. These are extremely relevant in biomedical and sustainable engineering contexts, but their design space is complexified by mechanical nonlinearities and inelastic behaviour.
This project aims to revolutionise the design of soft materials by leveraging Nature-derived principles. We will combine multiscale mechanical modelling, additive manufacturing, and AI to discover, implement, and validate novel concepts for soft materials. Target applications will range from biomedical scaffolds to garments and self-healing wearable patches, so that we welcome applicants from a wide range of disciplines.
About the Research Group:
We are broadly interested in the multiscale mechanics of highly deformable materials relying on fibre networks, such as several biological tissues, polymers, and textiles. A core area of interest directly relevant to this PhD project is the development of computational models with predictive or interpretative function, and the establishment of two-way links with corresponding experiments and additive manufacturing techinques. We are committed to offering an inclusive and collaborative research and learning environment that focuses on personal development of all members. Informal enquiries about potential applications are most welcome and shall be directed to Dr. Pensalfini (contact details provided below).
Candidate specification:
We welcome motivated candidates whose backgrounds and interests may include:
- Physics-based or data-driven computational modelling in structural mechanics
- Multiscale characterization and modelling of largely deformable materials
- AI-accelerated exploration of complex design spaces
- Formulation and solution of parameter identification or inverse design problems
- Bottom-up material design and their fabrication using additive manufacturing
- Proficiency in programming languages such as Python, MATLAB, and/or C/C++
- Proficiency in commercial finite element packages, e.g. Abaqus
The successful candidate will have the opportunity to fine tune the project based on individual interests and skills.
Relevant Bibliography:
[1] Barthelat, J Mech Phys Solids 73: 22–37, 2014. DOI: 10.1016/j.jmps.2014.08.008.
[2] Utama Surjadi et al., Nat Mater 24: 945–954, 2025. DOI: 10.1038/s41563-025-02219-5.
[3] Pensalfini et al., Phys Rev Lett 131: 058101, 2023. DOI: 10.1103/PhysRevLett.131.058101
Funding
Funded by: China Scholarship CouncilCandidate 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 Marco PENSALFINI.
Apply
Start an application for this studentship and for entry onto the PhD FT Medical Engineering full-time programme (Semester 1 / September start):
Please be sure to quote the reference "SEMS-PHD-689" to associate your application with this studentship opportunity.
| Related website: | https://www.sems.qmul.ac.uk/staff/m.pensalfini | |
| SEMS Research Centres: | ||
| Keywords: | Artificial Intelligence, Machine Learning, Biomedical Engineering, Mechanical Engineering, Solid Mechanics, Structural Mechanics, Polymers, Textiles, Computational Mathematics, Mathematical Modelling |