Professor

Rob Hewson

Has open position

Prof. at Imperial College London

Imperial College London

United Kingdom

Research Interests

Aerospace Engineering

10%

Metamaterial

10%

Python Programming

10%

Mechanical Engineering

10%

Machine Learning

10%

Reinforcement Learning

10%

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Positions(2)

Publisher
source

Ajit Panesar

Imperial College London

.

United Kingdom

PhD Studentship in Aeronautics: Architected Materials for Non-linear Thermo-mechanical Applications

[Full coverage of tuition fees and an annual tax-free stipend of £22,780 for Home, EU and International students.] This PhD studentship at Imperial College London offers an exciting opportunity to work at the intersection of aeronautics, mechanical engineering, materials science, and computer science. The project aims to develop architected materials and metamaterials with targeted non-linear thermo-mechanical responses, suitable for both terrestrial and aerospace applications. The research will integrate machine learning-based inverse design and topology optimisation to create multiscale materials capable of handling variability and uncertainty from sources such as material properties, fabrication processes, and boundary conditions. The successful candidate will build computational frameworks using advanced ML techniques, including tandem neural networks, video diffusion models, reinforcement learning, and mixture density networks, to efficiently explore high-dimensional design spaces and enable robust property-to-design mapping. The project is hosted by the IDEA Lab and Structural Metamaterials Group, which provide a collaborative and inclusive research environment, access to professional development, and opportunities to enhance both technical and interpersonal skills. Funding covers full tuition fees and a generous annual tax-free stipend of £22,780 for Home, EU, and International students. Applicants must hold or expect to hold a First class honours MEng/MSci or higher degree in Aeronautics, Mechanical Engineering, or Computer Science, and should have experience in machine learning, optimisation, Python, and finite element analysis. The studentship lasts 3.5 years, with a flexible start date between August 2026 and July 2027. The application process involves submitting a CV, transcripts, and a motivation statement for supervisor review, followed by a formal application for long-listed candidates. Imperial College London is committed to equality, diversity, and inclusion, supporting a welcoming environment for all researchers.

just-published

Publisher
source

Ajit Panesar

Imperial College London

.

United Kingdom

PhD Studentship in Aeronautics: Architected Materials for Non-linear Thermo-mechanical Applications

[Full coverage of tuition fees and an annual tax-free stipend of £22,780 for Home, EU and International students.] This fully funded PhD studentship at Imperial College London offers an exciting opportunity to work at the intersection of aeronautics, materials science, and machine learning. The project focuses on developing architected materials and metamaterials for non-linear thermo-mechanical applications, with a particular emphasis on aerospace and other demanding environments. You will join the IDEA Lab and Structural Metamaterials Group, collaborating in a world-leading research environment that values inclusivity and professional development. The research aims to fuse machine learning-based inverse design approaches with topology optimisation to create multiscale materials capable of targeted non-linear responses. You will develop computational frameworks that address variability and uncertainty in material properties, fabrication processes, and boundary conditions. The project leverages advanced techniques such as tandem neural networks, video diffusion models, and reinforcement learning to efficiently explore high-dimensional design spaces. Mixture density networks will be used to enable robust property-to-design mapping, overcoming limitations of deterministic ML methods and providing insights into reliability and diversity of inverse designs. Applicants should hold or expect to obtain a First class honours MEng/MSci or higher degree (or international equivalent) in Aeronautics, Mechanical Engineering, or Computer Science. Experience in machine learning, optimisation, Python programming, and finite element analysis is highly desirable. The studentship provides full coverage of tuition fees and a generous annual tax-free stipend of £22,780 for Home, EU, and International students, supporting you for 3.5 years of doctoral research. The application process involves submitting a CV, transcripts, and a motivation statement via the Supervisor Review Form by 8 January 2026. Supervisors will review applications and invite long-listed candidates to formally apply. For project-specific questions, contact Dr Ajit Panesar. Imperial College London is committed to equality, diversity, and inclusion, and offers a supportive environment for all researchers.

just-published