3.5 year D.Phil. studentship
Project: Interface Mechanics in Heterogeneous Materials: Influence of Defects, Impurities, and Rate-Dependent Behaviour
Supervisors: Dr Maria Lissner, Prof. Dan Eakins
We are seeking a highly motivated DPhil candidate to join our vibrant research group and engage in groundbreaking research at the intersection of impact engineering, fracture mechanics, and materials science. This project integrates experimental and computational mechanics with cutting-edge technologies like Machine Learning (ML), Artificial Intelligence (AI), and automation.
The demand for sustainable, high-performance engineering solutions is rising in sectors like automotive, aerospace, and human protection due to environmental and viability needs. Materials in extreme loading rate environments face drastic changes in stresses that exceed their mechanical properties, leading to deformation and fracture. With the increasing desire to use heterogeneous materials such as fibre-reinforced polymer composites, adhesive joints, and 3D printed polymers, understanding material characteristics like voids and imperfections and their influence on the damage initiation and failure is crucial. This is especially vital for predicting interfacial failure, such as in fibre-matrix interfaces and layer-by-layer interfaces in 3D printed polymers under extreme loading rate conditions.
By using a data-centric approach, this DPhil study provides a chance to leverage the advantages and opportunities of ML and AI to enhance the design and performance of materials for high-performance applications. Techniques will be developed to represent the probability and stochastic distribution of defects and impurities, integrating these into both analytical and numerical material models. Opportunities will be available to investigate material heterogeneity using advanced microscopy and X-ray technologies to analyse the stochastic distribution of the defects and impurities, establishing a foundation for data-centric mechanical approaches. By coupling these findings with suitable representation techniques, including AI and ML, the results will inform and advance material models. This will improve the understanding of defects and impurities of the bulk material and their influence on the interfacial damage initiation and failure mechanisms. Moreover, the DPhil study will explore the suitability of automation to enhance experiments and data collection processes in combination with numerical analysis.
If you are passionate about advancing sustainable engineering solutions and eager to work at the forefront of mechanics of materials, we encourage you to apply.
Eligibility
This studentship is funded through the Department of Engineering Science, University of Oxford and is open to Home students (full award – fees plus stipend).
Award Value
Course fees are covered at the level set for Home students (c. £10,070 p.a). The stipend (tax-free maintenance grant) is c. £19,237 p.a. for 3.5 years.
Candidate Requirements
Prospective candidates will be judged according to how well they meet the following criteria:
* A first class or strong upper second-class undergraduate degree with honours in Engineering, Applied Mathematics, Physics or Materials Science
* Excellent English written and spoken communication skills
The following skills are also highly desirable:
* Ability to program in Matlab, Python, or similar
* Laboratory-based skills
* Numerical modelling skills
Application Procedure
Informal enquiries are encouraged and should be addressed to Dr Maria Lissner (maria.lissner@eng.ox.ac.uk).
Candidates must submit a graduate application form and are expected to meet the graduate admissions criteria. Details are available on the course page of the University website.
Please quote 25ENGMM_ML in all correspondence and in your graduate application.
Application deadline: noon on 3 December 2024
Start date: October 2025
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