Research Associate in Machine Learning for Offshore Engineering

Location: South Kensington

About the role:

We are seeking a highly motivated researcher with a background in high performance computing and machine learning to join our team developing geometric digital twins for offshore wind turbine support structures, funded by a major EPSRC Open Plus Fellowship project led by Dr Adam Jan Sadowski. You will be primarily working on processing very large high resolution 3D point cloud laser scans of tower structures to abstract out and segment geometric features for the purposes of training predictive models that will then be used for high fidelity computational structural engineering.

What you would be doing:

You will join a team of primarily structural engineers working at Imperial’s Department of Civil and Environmental Engineering collaborating with Prof. Adrian Jackson and other colleagues at the Edinburgh Parallel Computing Centre. Your work would combine software and technique development which a focus on the processing of voluminous point cloud datasets (> 100 GB). Specifically, you will:

• Develop and train advanced models to perform statistically meaningful inpainting of regions of missing coverage
• Develop means of automated segmentation of the point clouds to isolate geometric features of interest for further dataset curation and training
• Develop tools which interface between the trained predictor / inference models and structural finite element model generators
• Collaborate with a multidisciplinary team of structural engineers, mechanical engineers and HPC specialists to ensure maximum impact including through dissemination in high impact journals.

What we are looking for:

• A PhD in High Performance Computing, Machine Learning, Computer Science, Applied Mathematics, Data Science, or equivalent research, industrial or commercial experience
• Practical experience with the core computing languages necessary for machine learning and high-performance computing, including C++, Python and CUDA
• Knowledge of machine learning, high performance computing and data science
• Excellent verbal communication skills and the ability to deal with a wide range of people
• Excellent written communication skills and the ability to write clearly and succinctly for publication

What we can offer you:

• Participation in a high-impact UK-led project with international collaborators that aims to develop the next generation of computational analysis tools for the study of massive-scale offshore metal wind support structures.
• The opportunity to continue your career at a world-leading institution and be part of our mission to continue science for humanity.
• Grow your career: gain access to Imperial’s sector-leading dedicated career support for researchers as well as opportunities for promotion and progression.
• Sector-leading salary and remuneration package (including 39 days off a year and generous pension schemes).
• Be part of a diverse, inclusive and collaborative work culture with various staff networks and resources to support your personal and professional wellbeing.

Further Information

This is a fixed-term full-time post for 24 months.

The estimated start date is January 2026, although this can be flexible depending on circumstances.

If you require any further details about the role, please contact:
Dr Adam Jan Sadowski at a.sadowski@imperial.ac.uk

Any queries regarding the application process should be directed to:
Briony Webb at b.webb@imperial.ac.uk. 

Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant.

Full information on the post is available in the job description.

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