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PhD Studentship: Federated Learning-Driven Decentralized AI Systems for Secure and Scalable Operations in Vehicular Networks

University of Plymouth - School of Engineering, Computing and Mathematics

Qualification Type: PhD
Location: Devon, Plymouth
Funding for: UK Students, EU Students, International Students
Funding amount: The studentship is supported for 3.5 years and includes Home tuition fees plus a stipend of £20,780 per annum 2025-26 rate
Hours: Full Time
Placed On: 27th February 2025
Closes: 28th March 2025

DoS: Dr Muhammad Asad (muhammad.asad@plymouth.ac.uk)

2nd Supervisor: Dr Haoyi Wang (haoyi.wang@plymouth.ac.uk)

3rd Supervisor: Dr Fatma Bouabdallah (fatma.bouabdallah@plymouth.ac.uk)

Applications are invited for a 3.5-year PhD studentship.

The studentship will start on 1st October 2025.

Project Description

Autonomous vehicles and smart transportation systems rely on artificial intelligence (AI) to process vast amounts of real-time data. Traditional AI models follow a central data collection approach, where raw data from multiple vehicles is continuously transmitted to a remote server for training and decision-making. This method introduces critical concerns. For example, privacy is compromised as sensitive data, including vehicle location, driving patterns, and sensor readings. Centralized storage also presents security risks, making data more vulnerable to cyberattacks and unauthorized access. Moreover, transmitting large datasets leads to high communication costs, increased bandwidth consumption, and potential delays in real-time decision-making.

This project aims to overcome these challenges by developing a federated learning-driven AI system that enables vehicles to collaboratively train models while keeping their data localized. By eliminating the need for centralized data transfer, federated learning preserves privacy, mitigates cybersecurity threats, and reduces communication overhead. However, real-world deployment comes with additional complexities, such as integrating diverse sensor data, optimizing AI models for vehicles with limited computing resources, and ensuring fast and reliable inter-vehicle communication.

The research will focus on designing privacy-preserving AI models and enhancing the efficiency of distributed learning in vehicular networks. It will integrate techniques from machine learning, deep learning, and network optimization to develop a scalable and secure AI framework for smart transportation. The successful candidate will work with experienced researchers, gain access to state-of-the-art computing resources, and contribute to high-impact publications. This project offers an exciting opportunity to develop AI-driven solutions that enhance autonomous driving, traffic safety, and smart mobility, shaping the future of intelligent transportation.

Eligibility

Applicants should have a first or upper second class honours degree in an appropriate subject and preferably a relevant Masters qualification. Applications from both UK and overseas students are welcome.

The studentship is supported for 3.5 years and includes full Home tuition fees, Bench fee plus a stipend of £20,780 per annum 2025/26 rate.  The studentship will only fully fund those applicants who are eligible for Home fees with relevant qualifications.  Applicants normally required to cover International fees will have to cover the difference between the Home and the International tuition fee rates.  The international component of the fee may be waived for outstanding international applicants.

There is no additional funding available to cover NHS Immigration Health Surcharge (IHS) costs, visa costs, flights etc.

NB: The studentship is supported for 3.5 years of the four-year registration period.

The subsequent 6 months of registration is a self-funded ‘writing-up’ period.

If you wish to discuss this project further informally, please contact:

Dr Muhammad Asad, Muhammad.asad@plymouth.ac.uk

To apply for this position please click on the Apply button above.

Please clearly state the name of the studentship that you are applying for on your personal statement.

Please see here for a list of supporting documents to upload with your application.

For more information on the admissions process generally, please contact research.degree.admissions@plymouth.ac.uk

The closing date for applications is 12 noon on 28th March 2025.

Shortlisted candidates will be invited for interview shortly thereafter.

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