Edge-to-Cloud Smart Mobility: AI Co-optimization for Future Autonomous Vehicles

Are you excited to contribute to a future of safe autonomous self-driving cars? Or are you fascinated to study the impact of autonomous vehicles mobility on cutting-edge computing infrastructures such as the edge-to-cloud continuum? This project is a unique opportunity to make both happen! <br /> <br /> Vision: Imagine yourself as a creator of a highly versatile coupled infrastructure of computing and vehicles, where computing &lsquo;follows&rsquo; vehicles, and vehicles &lsquo;follow&rsquo; computing! An infrastructure that is resilient, secure and self-adaptive to unanticipated changes, putting the foundations for meeting ambitious net zero targets! <br /> <br /> Methods and aim: Using advanced distributed Artificial Intelligence (AI) and optimization methods such as reinforcement, federated and collective learning, you will introduce techniques to load-balance the computational load within the edge-to-cloud continuum, as generated by new emerging mobility patterns of autonomous vehicles. With this load-balancing, passengers will experience higher safety and quality of services, such as augmented reality, by optimizing for lower latency, lower service violations and higher throughputs. Complementary, you will be introducing vehicle rerouting techniques that will prioritize for routes that do not overload computing infrastructures during computational offloading to preserve safety and quality of service. Ultimately, you will aim to unravel the interplay of these two coupled co-optimization processes and understand how to coordinate distributed resources for computing resources and transport systems. <br /> <br /> Opportunities for impact: This project provides unprecedented opportunities to make a PhD with impact on society. With well-established industrial collaborators, partnerships with policy makers and urban traffic control systems of cities and a large network of international collaboration partners, you will be in the strongest position to bring research in real-world, work with real-world data, and explore different prominent career development pathways. <br /> <br /> Team and supervision: This project also provides the opportunity to make your PhD with fun, by being integrated and supported within a creative, diverse and inclusive team of talented students and research fellows working on ambitious research projects such as a UKRI Future Leaders Fellowship. You will have strong supervision support by two experts in this area. This includes regular meetings, a tailored development plan, mentorship and coaching to deal with every challenge you will encounter during your PhD. <br /> <br /> This project will benefit from the following skills and knowledge: Solid software programming skills: Python, C, C++ or Java, UNIX and scripting skills, Strong knowledge of statistics, Knowledge of the foundations of distributed systems and AI.

<p class="MsoNoSpacing">Future smart mobility will include autonomous, shared and electric vehicles and the need to shift to low-transport carbon modalities to tackle climate change. However, existing information and communication technologies such as cloud computing cannot meet the requirements of this ambitious transition. This PhD project aims to create a self-adaptive infrastructure for smart mobility that will harvest computational resources within the edge-to-cloud continuum using distributed artificial intelligence and optimization methods such as reinforcement, federated and collective learning. As a PhD candidate in this project, you will be part of a creative and diverse team with excellent supervision, while you will collaborate with high-profile industrial partners that will unravel future career development opportunities and access to state-of-the-art technologies.</p> <p class="MsoNoSpacing">References</p> <ol> <li>Nezami, Z., Pournaras, E., Borzouie, A. and Xu, J., 2023. SMOTEC: An Edge Computing Testbed for Adaptive Smart Mobility Experimentation. arXiv preprint arXiv:2307.11181.</li> <li>Nezami, Z., Zamanifar, K., Djemame, K. and Pournaras, E., 2021. Decentralized edge-to-cloud load balancing: Service placement for the Internet of Things. IEEE Access, 9, pp.64983-65000.</li> </ol>

<p style="margin-bottom:11px">Formal applications for research degree study should be made online through the&nbsp;<a href="https://www.leeds.ac.uk/research-applying/doc/applying-research-degrees">University&#39;s website</a>. Please state clearly in the Planned Course of Study section that you are applying for <strong><em>PHD Computing FT,</em></strong>&nbsp;in the research information section&nbsp;that the research degree you wish to be considered for is&nbsp;<em><strong>Edge-to-Cloud Smart Mobility: AI Co-optimization for Future Autonomous Vehicles</strong></em> as well as <a href="https://eps.leeds.ac.uk/computing/staff/6446/dr-evangelos-pournaras">Dr Evangelos Pournaras</a>&nbsp;as your proposed supervisor and in the finance section, please state clearly&nbsp;<em><strong>the funding that you are applying for, if you are self-funding or externally sponsored</strong></em>.</p> <p>If English is not your first language, you must provide evidence that you meet the University&#39;s minimum English language requirements (below).</p> <p><em>As an international research-intensive university, we welcome students from all walks of life and from across the world. We foster an inclusive environment where all can flourish and prosper, and we are proud of our strong commitment to student education. Across all Faculties we are dedicated to diversifying our community and we welcome the unique contributions that individuals can bring, and particularly encourage applications from, but not limited to Black, Asian, people who belong to a minority ethnic community, people who identify as LGBT+ and people with disabilities. Applicants will always be selected based on merit and ability.</em></p> <p>Applications will be considered after the closing date. &nbsp;Potential applicants are strongly encouraged to contact the supervisors for an informal discussion before making a formal application. &nbsp;We also advise that you apply at the earliest opportunity as the application and selection process may close early, should we receive a sufficient number of applications or that a suitable candidate is appointed.</p> <p>Please note that you must provide the following documents in support of your application by the closing date of 3 April 2024 for Leeds Opportunity Research Scholarship or&nbsp;8 April 2024 for Leeds Doctoral Scholarship:</p> <ul> <li>Full Transcripts of all degree study or if in final year of study, full transcripts to date</li> <li>Personal Statement outlining your interest in the project</li> <li>CV</li> </ul>

Applicants to research degree programmes should normally have at least a first class or an upper second class British Bachelors Honours degree (or equivalent) in an appropriate discipline. The criteria for entry for some research degrees may be higher, for example, several faculties, also require a Masters degree. Applicants are advised to check with the relevant School prior to making an application. Applicants who are uncertain about the requirements for a particular research degree are advised to contact the School or Graduate School prior to making an application.

The minimum English language entry requirement for research postgraduate research study is an IELTS of 6.5 overall with at least 6.5 in writing and at least 6.0 in reading, listening and speaking or equivalent. The test must be dated within two years of the start date of the course in order to be valid. Some schools and faculties have a higher requirement.

<p><strong>Self-Funded or externally sponsored students are welcome to apply.</strong></p> <p><strong>UK</strong>&nbsp;&ndash;&nbsp;The&nbsp;<a href="https://phd.leeds.ac.uk/funding/209-leeds-doctoral-scholarships-2022">Leeds Doctoral Scholarships</a>&nbsp;and&nbsp;<a href="https://phd.leeds.ac.uk/funding/234-leeds-opportunity-research-scholarship-2022">Leeds Opportunity Research Scholarship</a>&nbsp;(open from October 2023)&nbsp;are available to UK applicants.&nbsp;<a href="https://phd.leeds.ac.uk/funding/60-alumni-bursary">Alumni Bursary</a>&nbsp;is available to graduates of the University of Leeds.</p> <p><strong>Non-UK</strong>&nbsp;&ndash; The&nbsp;<a href="https://phd.leeds.ac.uk/funding/48-china-scholarship-council-university-of-leeds-scholarships-2021">China Scholarship Council - University of Leeds Scholarship</a>&nbsp;is available to nationals of China (now closed for 2024/25 entry). The&nbsp;<a href="https://phd.leeds.ac.uk/funding/73-leeds-marshall-scholarship">Leeds Marshall Scholarship</a>&nbsp;is available to support US citizens.&nbsp;<a href="https://phd.leeds.ac.uk/funding/60-alumni-bursary">Alumni Bursary</a>&nbsp;is available to graduates of the University of Leeds.</p> <p><strong>Important:</strong>&nbsp; Any costs associated with your arrival at the University of Leeds to start your PhD including flights, immigration health surcharge/medical insurance and Visa costs are not covered under this studentship.</p> <p>Please refer to the&nbsp;<a href="https://www.ukcisa.org.uk/">UKCISA</a>&nbsp;website for information regarding Fee Status for Non-UK Nationals.</p>

<p style="margin-bottom:11px">For further information about this project, please contact Dr Evangelos Pournaras by email to&nbsp;<a href="mailto:E.Pournaras@leeds.ac.uk">E.Pournaras@leeds.ac.uk</a></p> <p>For further information about your application, please contact Doctoral College Admissions by email to <a href="mailto:phd@engineering.leeds.ac.uk">phd@engineering.leeds.ac.uk</a></p>