Research Assistant/Associate in Modelling Tow-Steered Composite Wing Structures
Develop AI and physics-based failure models for next-generation aircraft wings in collaboration with Airbus and industry partners.
Best for:Best for engineers and researchers with expertise in failure modelling of fibre-reinforced composites, finite element analysis (FEM), and AI-based computational methods, seeking industry collaboration and hands-on research experience in aerospace engineering.
Overview
This position at Imperial College London offers the opportunity to contribute to cutting-edge research in aerospace engineering, focusing on modelling tow-steered composite wing structures. The role involves developing advanced failure modelling methodologies for composite laminates, combining physically-based and AI-driven approaches. You will work closely with Airbus and iCOMAT, gaining hands-on experience in computational modelling, industry collaboration, and project management. The project aims to enhance structural efficiency in aerostructures, directly impacting future aircraft design. Ideal candidates will have expertise in failure modelling, finite element analysis (FEM), and AI applications in composites.
What you'll do
- Develop and implement physics-based failure models and AI-surrogates for tow-steered composite laminates, accounting for variable fibre orientations and stiffness distributions.
- Collaborate with Airbus and iCOMAT to understand manufacturing constraints and their impact on structural performance.
- Conduct research to improve structural efficiency in next-generation composite wing structures.
- Communicate research findings effectively to both academic and industry partners to inform future aerostructure design.
- Gain experience in project management, supervision, and international conference presentations.
- Travel to international conferences and industry partner sites to disseminate research outcomes.
Requirements
Degree required: PhD in Aerospace, Mechanical Engineering, or a closely related discipline, or equivalent research, industrial, or commercial experience. For Research Assistant roles, a first-class Master’s degree (or equivalent) in the same fields is required.
Language: English (proficiency expected for academic and industry communication)
Instruction: English
- Experience in failure modelling of fibre-reinforced composites using finite element methods (FEM)
- Practical experience with coding failure models for composites
- Knowledge of AI-based modelling techniques for fibre-reinforced composites
- Collaborative work experience in industry or academic settings
- No explicit nationality or residency restrictions mentioned
- Candidates without an officially awarded PhD may apply as Research Assistants
Funding & terms
How to apply
Deadline: 2026-10-20
Applicants must submit their CV, cover letter, and any relevant academic or professional documents through the Imperial College London job portal. Ensure your application highlights your experience in failure modelling, FEM, and AI-based methods for composites. For technical issues, contact support.jobs@imperial.ac.uk.
- CV
- Cover letter
- Academic or professional transcripts (if applicable)
- References (if required)
Contact
Silvestre Pinho· Contact for further details
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