A fully funded PhD opportunity at Cranfield University focusing on developing AI-driven cognitive navigation systems for autonomous transport. This project integrates multi-sensor fusion, AI, and resilient Position, Navigation, and Timing (PNT) architectures to enable safe navigation even in GNSS-denied environments.

Important Information Table

Overview

Cranfield University invites applications for a fully funded PhD studentship focused on developing AI-driven cognitive navigation systems capable of operating reliably in complex and GNSS-challenged environments. Sponsored by the EPSRC Doctoral Landscape Awards (DLA), Cranfield University, and Spirent Communications, this project aims to design intelligent, resilient positioning and navigation architectures for next-generation autonomous systems.

As autonomy becomes increasingly embedded in modern mobility, ensuring the robustness of Position, Navigation and Timing (PNT) systems is vital. Traditional GNSS-based navigation is vulnerable to interference, jamming, and signal degradation, creating significant safety challenges. This PhD explores advanced solutions using AI, multi-sensor data fusion, cognitive decision-making, and resilient PNT technologies.

Project Description

The project will develop a smart cognitive navigation framework capable of interpreting and fusing data from multiple sensor sources—including radio signals, inertial sensors, and onboard systems—to deliver reliable navigation even when satellite-derived information is limited or unavailable.

Your research will focus on:

• Designing adaptive AI-driven algorithms for multi-sensor fusion

• Developing cognitive navigation systems that learn and make autonomous decisions

• Ensuring robust PNT performance under uncertainty or GNSS denial

• Implementing real-time AI architectures for autonomous transport platforms

• Testing and validating navigation technologies using advanced simulation tools

The project is aligned with the UK’s Net Zero Transport Strategy, supporting safer, efficient, and sustainable autonomous mobility.

Industry Collaboration

This PhD is co-sponsored by Spirent Communications, a global leader in navigation and testing technologies.
You will benefit from:

• Access to cutting-edge simulation environments

• Industry mentorship and technical support

• Two fully supported industry placements

• High-value datasets and real-world validation platforms

Training & Research Environment

Cranfield University is internationally recognised for applied research, engineering excellence, and strong industry partnerships. As part of the Cranfield Doctoral Network, you will join an active research community, participate in interdisciplinary collaborations, and benefit from:

• Training in software-defined radio

• Advanced AI methods

• Hardware-in-the-loop testing

• Project management and scientific writing workshops

• Conference participation and publication opportunities

This PhD equips graduates with strong pathways into academia, aerospace, autonomous systems, robotics, and emerging navigation technologies.

Entry Requirements

Applicants should have:

• A first or second-class UK honours degree (or equivalent) in:

  • Aerospace Engineering

  • Robotics

  • Computer Science

  • Electrical/Electronic Engineering

  • Related fields

• Programming experience in Python or MATLAB

• Knowledge of robotics, AI, sensor fusion, or signal processing

• Hands-on experience with embedded systems or autonomous platforms is desirable

• Must qualify as a Home student with no UK residency restrictions

Cranfield University values diversity and encourages applications from underrepresented groups, including neurodiverse individuals and students with disabilities.

How to Apply

If eligible, applicants should submit the online application form through the official Cranfield University portal.

Contact Information:
Name: Dr. Mengwei Sun
Email: Mengwei.sun@cranfield.ac.uk
Phone: +44 07594731903