This PhD scholarship is part of the EU Horizon Europe Marie Skłodowska‑Curie Actions Doctoral Network (MSCA DN) project ANT - Embedded AI Systems and Applications (https://ant-dn.eu/). Research Assistant (MSCA) with a PhD full scholarship on Networked Scalable Learning - 16044 Department of Computer Science College of Engineering, Design and Physical Sciences Location: Brunel University of London, Uxbridge Campus Salary: £40,757 per annum inclusive of London Allowance The University will waive international PhD tuition fees for the duration of the program. Hours: Full-time Contract Type: Fixed-term for 29 months, followed by a 7-month stipend at the UKRI rate (currently approximately £1,983.75 per month, subject to adjustment in line with UKRI rates), covering the full duration of the PhD. Brunel University of London was established in 1966 and is a leading multidisciplinary research-intensive technology university delivering economic, social and cultural benefits. The Department of Computer Science where this project will be conducted is ranked 3rd in the UK (2020-22) overall in the NTU Performance Ranking of Scientific Papers for World Universities and, for five years in succession, 1st in the UK for H-index and Highly Cited Papers (2018-2022). According to the recently released 2023 Shanghai Academic Ranking of World Universities (ARWU) Computer Science & Engineering at Brunel has been ranked 7th in the UK and a very respectable 101-150 position worldwide. This PhD scholarship is part of the EU Horizon Europe Marie Skłodowska‑Curie Actions Doctoral Network (MSCA DN) project ANT - Embedded AI Systems and Applications (https://ant-dn.eu/). The ANT project is a large-scale international doctoral training program, offering 18 fully funded PhD positions with a total budget of €4.9 million, aimed at advancing research in embedded and networked AI systems. Expected Results: 1) Networked scalable learning techniques that accommodate the dynamic topology, computing loads, data volume, resource availability and quality of service (QoS) requirements; 2) Network protocols to facilitate networked scalable learning; 3) Optimisation schemes for dynamic resource allocation and computing load distribution. Planned secondments: ST (3 months, M16-M18, may be rescheduled): Networked scalable and continual learning in dynamic evolving environment IMEC (4 months, M27-M30, may be rescheduled): Efficient data transfer protocols for networked scalable learning Candidate profile: computer science, machine learning, electrical engineering, telecommunication engineering, applied mathematics, or related areas. Desirable skills/interests: machine learning, large language model, large AI model, signal processing, wireless communications, applied optimisation We offer a generous annual leave package plus discretionary University closure days, excellent training and development opportunities, as well as a great occupational pension scheme and a range of health-related support. The University is committed to a hybrid working approach. Family allowance may be payable on eligibility and supporting evidence. Research training and network fees are available up to £50,139.84 for 3 years. Appointment to this post is subject to the successful applicant holding the appropriate permission to work in the UK, and an ATAS certificate may be required depending on nationality. The university may provide support for applying for a Global Talent Visa. For an informal discussion, please email Professor Kezhi Wang at Kezhi.Wang@brunel.ac.uk Closing date for applications: 21 May 2026 For further details about the post including the Job Description and Person Specification and to apply please visit https://careers.brunel.ac.uk If you have any technical issues please contact us at: hrsystems@brunel.ac.uk Brunel University of London is fully committed to creating and sustaining a fully inclusive workforce culture. We welcome applicants from all backgrounds and communities, we particularly welcome applicants who are currently under- represented in our workforce.