Program Overview

Secure and Trustworthy AI-Electronics: Hardware-Embedded Intelligence for Safety-Critical Systems PhD

This PhD opportunity at Cranfield University invites candidates to pioneer research in embedding AI into electronic hardware to enhance security and trustworthiness in safety-critical systems. The project delves into areas such as hardware-based security measures, tamper detection, and the integration of explainable AI models within embedded platforms.

Research Focus Areas

• Hardware Security Primitives: Develop foundational security elements like Physical Unclonable Functions (PUFs) and True Random Number Generators (TRNGs) to secure hardware components.
• Embedded Trust Protocols: Design protocols that establish and maintain trust within AI-electronic systems, ensuring secure communication and operation.
• Side-Channel Attack Mitigation: Implement techniques to protect systems against side-channel attacks, safeguarding sensitive information from unintended data leakage.
• Communication Resilience Against Jamming and Spoofing: Develop AI-driven methods to detect and mitigate jamming and spoofing attacks, enhancing the robustness of communication infrastructures in critical applications.
• Trusted Execution Environments (TEEs): Explore the implementation of TEEs, such as ARM TrustZone, to create secure zones within embedded systems, ensuring that sensitive operations are isolated and protected from potential threats.

About Cranfield University

Cranfield University offers a distinctive research environment renowned for its world-class programmes, cutting-edge facilities, and strong industry partnerships, attracting top-tier students and experts globally. As an internationally recognised leader in AI, embedded system design, and intelligent systems research, Cranfield fosters innovation through applied research, bridging academia and industry.

Facilities and Resources

The project will be conducted within Cranfield's Integrated Vehicle Health Management (IVHM) Centre, which provides access to state-of-the-art laboratories, hardware/software resources, and design facilities, supporting AI-powered electronics research. The IVHM Centre is globally recognized for defining the subject area and continues to expand its research horizons.

Project Outcomes

The project addresses the growing need for security in AI-integrated electronic systems. Research will focus on developing hardware security primitives, embedded trust protocols, and techniques to mitigate side-channel attacks and tampering. Additionally, the project will explore secure communication infrastructures to protect against jamming and spoofing attacks. Outcomes will include the design of robust, trustworthy systems suitable for deployment in sensitive environments such as defence, finance, and critical infrastructure, ensuring data integrity and system reliability.

Career Prospects

Graduates from this programme will become experts in hardware-based trust mechanisms, secure AI integration, and attack resilience. The experience of working with real attack vectors, cryptographic primitives, and tamper-evident architectures will sharpen their ability to design trustworthy electronics at scale. In parallel, students will strengthen analytical reasoning, ethical decision-making, secure systems thinking, and research dissemination skills. These capabilities are directly transferable to careers in cybersecurity R&D, secure hardware design, defence electronics, and post-quantum technology innovation, where demand for secure and intelligent electronics continues to grow.

At a Glance

• Application deadline: 25 Mar 2026
• Award type(s): PhD
• Start date: 01 Jun 2026
• Duration of award: 3 years Full-time
• Eligibility: UK, Rest of world, EU
• Reference number: SATM587

Entry Requirements

Applicants should have a first or second class UK honours degree or equivalent in a related discipline. This project would suit individuals with a background in computer engineering, electronic engineering, information security, or physics—especially those with experience in cybersecurity, cryptography, or secure system design. Prior exposure to digital design (Verilog/VHDL), AI hardware accelerators, or FPGA/ASIC development is advantageous but not essential.

Funding

Self-funded.

Cranfield Doctoral Network

Research students at Cranfield benefit from being part of a dynamic, focused, and professional study environment and all become valued members of the Cranfield Doctoral Network. This network brings together both research students and staff, providing a platform for our researchers to share ideas and collaborate in a multi-disciplinary environment. It aims to encourage an effective and vibrant research culture, founded upon the diversity of activities and knowledge. A tailored programme of seminars and events, alongside our Doctoral Researchers Core Development programme (transferable skills training), provide those studying a research degree with a wealth of social and networking opportunities.