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Ajit Panesar

Top university

10 months ago

PhD Studentship in Aeronautics: Architected Materials for Non-linear Thermo-mechanical Applications Imperial College London in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Expired

Country flag

Country

United Kingdom

University

Imperial College London

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Keywords

Computer Science
Machine Learning
Mechanical Engineering
Materials Science
Aerospace Engineering
Python Programming
Reinforcement Learning
Artificial Neural Network
Multiphysics Simulation
Metamaterial

About this position

[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.

Funding details

Available

What's required

Applicants must have achieved or be expected to achieve 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, and finite element methods is highly desirable. Due to the competitive nature of the studentship, strong academic performance and relevant technical skills are required.

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Professors

Prof. at Imperial College London

University Name
Country flag

United Kingdom

Research Interests

Aerospace Engineering

Mechanical Engineering

Computer Science

Materials Science

Mathematics