Applications are invited for a PhD degree in Artificial Intelligence and Machine Learning (AI/ML) to advance the security and reliability of cyber-physical systems, embedded systems, and electronics/electrical systems. The research would focus on building advanced machine learning techniques and edge AI modelling for moving to the next generation of secure and reliable electronic networking specific to applications in the automotive industry.

The rising connectivity exposes vehicular communication systems to a variety of cyberattacks. The problem is racketing in the automotive sector because vehicles are equipped with many Electronic Control Units (ECUs – small devices controlling a specific function, e.g., engine control, telematics control, airbag, and breaks) communicating via electronic networks such as the widely used Controller Area Network (CAN). Superior robustness, flexibility, speed, low cost, and built-in error detection properties are among many recognised advances for ECUs and CAN-Bus systems. However, they all in common were designed for a high level of reliability and fault tolerance, while less attention was taken concerning security and data integrity in response to the growing cyberattack surface, which is today’s primary concern. A solution to overcome the problem, as led by industries, is the development of Intrusion Detection and Prevention Systems (IDPS), which is a supervisory module proposed for identifying CAN network malicious messages without modifying legacy ECUs and causing high traffic overhead. The traditional IDPS approaches lead to high false alarm rates, whereas state-of-the-art solutions may suffer from vehicle dependency. This research aims to benefit from machine learning and artificial intelligence techniques for enhancing Intrusion Detection and Prevention Systems, implementable on Edge AI devices.

With this research, you will study vehicular communication systems, state-of-the-art car hacking scenarios, threat detection and mitigation approaches. Further, you would contribute to the cybersecurity of in-vehicle communication systems by exploring Artificial-Intelligent techniques for analysing the test results from a wide range of car hacking use cases.

The proposed research aims to develop a novel integrated approach to building resilient and trustworthy in-vehicle communication systems by designing and architecting an IDPS for application in automotive. It facilitates incorporating cyber security for automotive sectors in complying with UNECE WP.29 regulations (United Nations Economic Commission for Europe) planned to be executed by governments and car manufacturers. Therefore, this research revolutionises electronic networking for vehicular applications by building on the state-of-the-art technology developed by academics and industries in equipping systems with capabilities featured from IDPS facilitating AI techniques for detecting and mitigating threats. It provides robust and comprehensive security schemes for electronic networks in response to the broad range of hacking scenarios that automotive industries face nowadays. The research will contain experiments mapping the automotive sector; state-of-the-art CAN vulnerabilities recognised by car manufacturers.

Cranfield is a unique learning environment with world-class programmes, unrivalled facilities and close links with business, industry and governments, all combining to attract the best students and teaching staff worldwide. In 2014, 81% of research at Cranfield was rated as world-leading or internationally excellent in the Research Excellence Framework (REF).

The Integrated Vehicle Health Management (IVHM) Centre is in its 14th year of operation. Founded by Boeing and a number of aerospace partners (BAE Systems, Rolls-Royce, Meggitt and Thales) in 2008, it has grown to perform work in sectors such as transport, aerospace, and manufacturing. The Centre integrates a multidisciplinary research effort to develop cost-effective component and system health management technologies capable of supporting ground and on-board applications of high-value, high-complexity systems. IVHM Centre is a member of the Digital Aviation Research and Technology Centre (DARTeC), which focuses its research on aircraft electrification, connected systems, unmanned traffic management, seamless journey, distributed airport/airspace management, and conscious aircraft. Research England, Thales, Saab, Aveillant IVHM Centre and Boxarr are some of the prominent members of DARTec. IVHM Centre also works in close collaboration with Aerospace Integration Research Centre (AIRC), founded in partnership with Airbus and Rolls-Royce. The potential PhD candidate will have access to the facilities held by AIRC and DARTeC in addition to having interactive sessions with experts at AIRC and DARTeC.

IVHM hosts a number of research groups, including ‘Reliable and Secure Electronic Design (Seretonix), which focuses on research in the area of electronic health management, hardware root of trust, smart instrumentation, and secure vehicular communication systems. IVHM is also an active member of Europractice, a consortium of European research organisations supporting academic institutions with access to CAD tools, IC prototyping services, system integration solutions, training activities and possibilities for small volume production. It allows wider adoption of state of the art microelectronics and electronic system design methodologies and technologies. It enables IVHM to provide students with excellent technical support (hardware and software) and training courses based on the needs of the research and availability of the courses within the UK or EU.

The successful culmination of this project envisages the availability of an efficient and intelligent security regime for highly future innovative connected vehicles involving embedded systems communicating through electronic networks supervised by AI-Optimised IDPS. It enhances the security of electronic networking over its entire operational service life. Also, the AI-based built-in IDPS would serve as a benchmark for other high-end platforms requiring alternative networking protocols, e.g., MIL-STD-1553, AFDX/ARINC 664, ARINC 429/629, CAN, TTP, for intense use in marine, commercial aviation, military aviation, automotive sectors; respectively.

The project will provide active collaboration and exchange of ideas and knowledge with key stakeholders within different centres of the Cranfield University, industrial partners in the automotive industry, Seretonix’s industrial contacts, including NXP Semiconductor (CAN Bus market leader), iQuila (technology leader in secure network solution for automotive sectors), and Quantum Dice (Oxford University’s world-renowned quantum optics lab leading Quantum Cyber Security). The paraphernalia of electronic networking, IDPS, AI and Machine Learning based applications within the IVHM centre and across other research centres would be helpful for the potential researcher in acquiring essential knowledge and building skills (e.g., embedded electronic design and AI algorithms’ formulation) required for this specific research project. The IVHM Centre encourages and supports ample opportunities to disseminate individual research through reputed journals and present papers in high profile and well-known IEEE conferences within the UK and across the globe. It also provides a networking platform for promising researchers to lay the foundations of their professional relationships with key representatives from various companies. More significantly, the potential candidate will have the opportunity to present his research work during quarterly technical reviews to the wider research community from within the university and the industrial partners (Boeing, Thales, Airbus, and BAE Systems).

Upon successful completion of the project, the potential candidate will be able to carry out research activities independently and more vigorously. This research will be formative for the potential candidate in building his/her skills in understanding automotive systems, threats analysis, data analytics AI/ML techniques, analytical logic and algorithm craftsmanship. Understanding the essence and application of futuristic secure electronic system design would broaden the employability scope appreciably.

At a glance

  • Application deadline29 Jan 2023
  • Award type(s)PhD, MSc by Research
  • Start date28 Feb 2023
  • Duration of award3 years
  • EligibilityUK, EU, Rest of World
  • Reference numberSATM281

Entry requirements

Applicants should have a first or second class UK honours degree or equivalent in a related discipline. This project would suit:

  • graduate and postgraduate students with a degree in engineering (preferably in electrical/electronic/mechanical/aerospace/or computation), data science, or any other related physical sciences subject.
  • Researchers and Engineers with a background/interest in automotive, electronics and electrical systems evaluation concerning cybersecurity. PhD candidates must have software programming skills (intermediate to advanced level) and familiarity with AI and Machine Learning methods.

Above all, research aspirants with innovative approaches, high motivation and willingness to learn are encouraged to apply.


This is a self-funded opportunity so the student would need to source their own funding. However, a bursary can be considered for an exceptional candidate. The application is open to UK and international students.

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.

How to apply

If you are eligible to apply for this research studentship please complete the application form below:

Online application form for PhD 

For further information please contact - Dr Mohammad Samie