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University of Southampton

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PhD in Advanced Machine Learning for Helicopter Flight Test Data Analytics University of Southampton in United Kingdom

Degree Level

PhD

Field of study

Computer Science

Funding

Full funding available

Deadline

Aug 25, 2026

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Country

United Kingdom

University

University of Southampton

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Keywords

Computer Science
Mechanical Engineering
Electrical Engineering
Aerospace Engineering
Mathematics
Artificial Intelligence
Pattern Recognition
Time Series Analysis
Engineering Mathematics
Clustering Algorithms
Text Classification
Machine learning

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About this position

PhD opportunity at the University of Southampton in Advanced Machine Learning Framework for Helicopter Flight Test Data Analytics.

This project sits at the intersection of Aerospace Engineering, Computer Science, Mechanical Engineering, and Engineering Mathematics. The research focuses on turning large, heterogeneous helicopter flight-test datasets into a structured, queryable, and predictive system using machine learning and artificial intelligence.

Key topics include automated data preprocessing, synchronization of multi-source onboard signals, unsupervised and supervised learning for manoeuvre cataloguing, and engineering models for power requirements, trim maps, vibrations, and fuel consumption. The project also emphasizes traceability, reproducibility, and interpretable methods rather than black-box modelling, with integration into existing Leonardo Helicopter Division workflows.

Supervisory team: Prof. Andrea Da Ronch and Prof. Simon Cox.

Funding: competition-funded PhD project; tuition fees are covered and a tax-free living stipend is provided.

Eligibility: applicants should hold a UK 2:1 honours degree or international equivalent. An English language qualification is required if applicable.

How to apply: submit an online application, choose Research, 2026/27, Faculty of Engineering and Physical Sciences, select Full time, and search for PhD Engineering & the Environment (7175). Add the supervisor name in section 2 and include a CV, two academic references, transcripts/certificates, and English language evidence if needed.

Deadline: 2026-08-25.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

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