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PhD Studentship: Ubiquitous Cognitive Navigation with AI Based Systems
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PhD Studentship: Ubiquitous Cognitive Navigation with AI Based Systems
Cranfield University
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Qualification Type: PhD
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Location: Cranfield
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Funding for: UK Students
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Funding amount: £24,000
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A bursary of up to £24,000 (tax free) plus fees for three and a half years.
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Hours: Full Time
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Placed On: 23rd June 2026
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Closes: 21st September 2026
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Reference: CRAN-0091
This fully-funded PhD studentship, sponsored by the EPSRC Doctoral Landscape Awards (DLA), Cranfield University and Spirent Communications, offers a bursary of £24,000 per annum, covering full tuition fees. This PhD project in the area of autonomy, navigation and artificial intelligence, aims to advance the development of intelligent and resilient navigation systems for autonomous transport. While autonomy is becoming more integrated into modern mobility, the reliability of Position, Navigation and Timing (PNT) systems—especially in environments where GNSS signals are denied or degraded—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient operation of autonomous systems in complex, real-world conditions.
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This PhD project aims to develop resilient Position, Navigation and Timing (PNT) systems for autonomous transport, addressing a critical challenge in the UK's Net Zero transition. Current satellite dependent navigation remains vulnerable to interference, jamming and signal degradation, causing serious problems for safe and efficient transport. By integrating artificial intelligence (AI), multi-sensor fusion, and cognitive systems, the research will pioneer robust navigation architectures. These improvements are key to making future transport systems safer, more efficient, and more sustainable.
The aim of this project is to design a smart cognitive navigation framework that information from various sensors and learn to make decisions on its own. It will use signals from different sources—such as radio signals and internal sensors— to maintain robust and accurate PNT, even when satellite signals are weak or missing. A built-in intelligent system will manage and adjust the way information is used in real time.
The project is co-sponsored by Spirent Communications, a world leader in navigation and testing technology.
The project will advance intelligent and resilient navigation systems, contributing to the UK’s Net Zero transport strategy. Outcomes will include novel AI algorithms, validated navigation architectures, and new insights into next-generation intelligent mobility solutions.
The student will undertake two industry placements at Spirent, use high-tech simulation equipment, and have access to valuable industry data. The student will benefit from opportunities to present at leading international conferences. Additional training in software-defined radio, hardware-in-the-loop testing, and advanced AI methods will further enrich the student’s research experience.
- Application deadline: 30 Sep 2026
- Start date: 25 Jan 2027
- Duration: 3.5 years
- Eligibility: UK
- Reference: CRAN-0091
Entry Requirements
Applicants should have a first or second class UK honours degree or equivalent in a related discipline. This project would suit someone with:
- Experience with programming (Python, MATLAB),
- Background in aerospace, computer science, robotics, or electrical engineering graduates,
- Hands on skills in implementation of fusion/learning based techniques in the areas of robotics, or autonomous systems,
- Interested in autonomous systems and signal processing,
- Keen to work with equipment and embedded platforms
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Funding
Sponsored by EPSRC, Spirent Communications PLC and Cranfield University, this DLA studentship will provide a bursary of up to £24,000 (tax free) plus fees* for three and a half years.
To be eligible for this funding, applicants must be classified as a Home fee status student.
How To Apply
For further information please contact:
- Name: Dr Mengwei Sun
Email: Mengwei.sun@cranfield.ac.uk - Name: Prof Ivan Petrunin
Email: i.petrunin@cranfield.ac.uk
If you are eligible to apply for this studentship, please complete the online application form via the above 'Apply' button.
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