PhD in Edge and Cloud AI

PhD pathways

Pursuing a PhD with researchers from the National Edge AI Hub offers an unparalleled opportunity to engage with cutting-edge advancements in computing (Cloud-Edge-IoT Continuum) and Artificial Intelligence (AI). It is the only national research centre in the UK, funded by the UK government, that addresses critical challenges in deploying AI at the edge and its continuum. It ensures AI algorithms’ safety, resilience, and efficiency in real-world, distributed environments. Students benefit from working alongside world-renowned edge computing, distributed systems, and AI experts, contributing to impactful research projects funded by prestigious organisations like UKRI and DSIT. The Hub’s strong partnerships with academia and industry provide access to state-of-the-art technologies and resources, enabling students to test and implement their solutions in high-impact, real-world scenarios. 

The Hub fosters a collaborative and interdisciplinary research environment where PhD candidates are immersed in a vibrant ecosystem combining theoretical innovation and practical application. Its focus on tackling grand challenges—such as safeguarding AI systems against cyber-attacks and managing resource constraints in heterogeneous networks—ensures that students address problems of high societal relevance. Furthermore, the Hub’s commitment to producing high-quality publications and delivering tangible impact amplifies the visibility of its researchers in both academic and industrial circles. This creates a unique platform for PhD candidates to build a robust research profile while contributing to pioneering advancements that shape the future of AI and edge computing.

Why choose the National Edge AI Hub for your PhD?

  • Mentorship by Global Experts: Train under world-renowned leaders in edge computing and AI, including IEEE Fellows, ranked among the top globally for impact in distributed systems research.
  • Exclusive Research Network: Unlock internship opportunities with our network of 60+ industry partners and 12 leading universities, ensuring hands-on experience and career-ready skills.
  • Access to Elite Computing Facilities: Leverage cutting-edge infrastructure, including state-of-the-art server rooms and high-performance computing tailored for advanced research.
  • Real-World Experimentation: Conduct groundbreaking research on premier testbeds like the Newcastle Urban Observatory (https://newcastle.urbanobservatory.ac.uk/)—the UK’s largest urban sensing network—perfect for real-time edge computing projects.
  • Shape the Future of AI: Be at the forefront of solving global challenges in edge AI safety, resilience, and scalability while building a standout research profile with high-impact publications.

Research Areas

  • Distributed AI Training in Hybrid Cloud-Edge-IoT  Infrastructures
  • Cloud application engineering using low-code/no-code abstractions.
  • Application Migration Techniques in Cloud-Edge-IoT Continuum
  • Renewable Energy Source-aware Cloud Datacentre Management
  • AI Model Optimisations on Resource-Constrained Edge Devices
  • AI Model Quality Certification
  • AI, Machine Learning, and Deep Learning Architectures
  • Cybersecurity in Cloud-Edge-IoT Continuum
  • Fault Management in Cloud-Edge-IoT Continuum
  • Digital Twins and Artificial Intelligence
  • Data Flow Orchestration in Cloud-Edge-IoT Continuum
  • Zero Trust Cloud-Edge-IoT systems
  • AI technology acceptance, adoption, implementation and diffusion
  • Secure Multi-party Computation on the edge
  • Secure Federated learning 
  • Acoustic and RF side-channel attacks on edgeAI models
  • Power-analysis attacks and defenses
  • Vehicular security 
  • Quantum Machine Learning

Available opportunities

1. Self-funded Scholarship

2. Commonwealth Scholarships

  • Eligibility: Students from Commonwealth countries.
  • Course: MSc, PhD, Professional
  • Funding: Most scholarships are fully funded, which means that as well as covering your tuition fees, you will also receive your airfare to and from the UK and a living allowance to support you while you are here. 
  • Details: Aimed at promoting higher education in Commonwealth member states.
  • Website: https://study-uk.britishcouncil.org/scholarships-funding/commonwealth-scholarships

3. Chevening Scholarships

4. China Scholarship Council (CSC) – Newcastle University and Cardiff University 

  • Eligibility: Chinese nationals applying for postgraduate research (PhD) at Newcastle University or Cardiff University.
  • Course: PhD
  • Funding: Fully funded scholarships that cover tuition fees, monthly stipend, health insurance and return international airfare.
  • Details: The CSC collaborates with UK institutions like Newcastle University to support Chinese students pursuing advanced research. Applicants must secure an offer of admission from Newcastle University and then apply for the CSC funding.
  • Website: https://www.ncl.ac.uk/mediav8/modern-languages/files/csc-nu-phd-scholarships-regulations-22-23.pdf

5. Fulbright Scholarship

  • Eligibility: International students meet the Fulbright Commission’s requirements in their home countries. Criteria often include academic excellence, leadership potential, and cultural engagement.
  • Course: Master’s, PhD. Specific funding for PhDs depends on the country-specific Fulbright Commission.
  • Funding: Fully funded including tuition fees, monthly stipend, health insurance and travel expenses.
  • Details: A globally recognised scholarship fostering cross-cultural exchange and academic collaboration. 
  • Website: https://fulbright.org.uk/going-to-the-uk/

6. Newcastle University Overseas Research Scholarship

7. Industry Scholarship: e.g., Google PhD Fellowship, Nvidia Graduate Fellowship

Supervisors

Professor Rajiv Ranjan, Newcastle University

Pursuing a PhD with researchers at the National Edge AI Hub means working with world-leading experts like Prof. Rajiv Ranjan, whose transformative contributions to Distributed Computing and AI systems are internationally recognised. A Fellow of the IEEE, the Academy of Europe, and AAAI, Prof. Ranjan is ranked #4 globally for citation impact in distributed systems by Stanford University and #15 by Scopus. His groundbreaking work has earned three IEEE Research Excellence awards, over eight Best Paper Awards, and funding for interdisciplinary UKRI projects exceeding £34M. He exemplifies the calibre of mentorship and impact awaiting students at the Hub with over 350 highly cited publications and a citation record with a Google Scholar h-index of 80 and 32,500+ citations. He has published his research in top-quality (CORE A*) journals and conferences, including IEEE TPDS, IEEE TC, ACM WWW, and VLDB, among many others.

Dr. Aydin Abadi is an Assistant Professor (lecturer) in Cybersecurity at Newcastle University, specializing in privacy-enhancing technologies, cryptography, blockchain, and financial fraud prevention. He earned his PhD in Secure Multi-Party Computation from the University of Strathclyde, where he was awarded the Euan Minto Prize in 2015 for the best paper authored by a research student. Prior to his current role, Dr. Abadi served as a Senior Research Fellow at University College London, leading the STARLIT project, which won joint first prize in the UK-US Privacy Enhancing Technologies Prize Challenge in 2023. His STARLIT project has been cited by the White House and UK government websites. As a Programme Committee (PC), he serves various top-tier conferences such as ACM CCS 2025 and WWW 2023. Dr. Abadi’s research focuses on developing secure and efficient mechanisms such as privacy-preserving machine learning and cryptographic protocols to address data privacy and security challenges.

Dr. Mujeeb Ahmed is a Senior Lecturer in computing at the Newcastle University, UK. His research interests are in the security of Cyber-Physical Systems (CPS), the Internet of Things (IoT), Communication Systems, and Critical Infrastructures. He was a Presidential Graduate Fellow for the Ph.D. program at the SUTD. Mujeeb has been a visiting fellow at the EECS department at the Georgia Institute of Technology. His work has been awarded the Best Paper award at ACM CPSS 2020, the best research project SoilBuild award at FIRST 2020 and the Kulicke and Soffa Award 2018. As a PhD student, you will work with Dr. Ahmed on IoT/CPS Security and Privacy and Machine Learning Applied to Cyber-Physical Systems.

Dr Jonte R Hance has already published 24 research articles (18 as first author), in journals including Nature Physics, npj Quantum Information, JPhys Photonics, and Quantum Science and Technology, despite having only been awarded their PhD in March 2023. These explored both foundational and applied topics in quantum information science and technologies. They have just been awarded a £1.7 million fEC EPSRC Quantum Technologies Career Acceleration Fellowship, to fund half their time plus 2 PDRAs, for 5 years, as well as a £28k Royal Society Research Grant. They have also joined as a late Researcher Co-Lead on the £13 million EPSRC National Edge AI Hub, to set up a Quantum Machine Learning Research Theme. They are keen to support students interested in working at the intersection of quantum technologies and machine learning/AI.

Dr Dev Jha is a Lecturer at the School of Computing, Newcastle University. He is also a visiting researcher at the University of Oxford. His research interests include cloud continuum, zero trust architecture, trusted computing and quantum computing. Before joining Newcastle University, he was a postdoctoral research associate jointly with the University of Oxford and CyberHive Ltd. He is currently collaborating with various Industry partners including AMD and Horiba Mira. Dev has published in many top conferences and journals including WWW, ACM Middleware, ACM HPDC, IEEE CCGrid, IEEE Cloud, IEEE Transactions on Parallel and Distributed Systems, IEEE Transactions on Cloud Computing and IEEE Transactions on Sustainable Computing. He is currently an associate editor of Springer Nature Computer Science and TPC member of more than 10 conferences including IEEE Cloud, IEEE CCGrid and IEEE WCNC. 

Carsten Maple is the Director of the NCSC-EPSRC Academic Centre of Excellence in Cyber Security Research and Professor of Cyber Systems Engineering at the University of Warwick. He is also Director for Research Innovation at the National Edge AI Hub, was a co-investigator of the PETRAS National Centre of Excellence for IoT Systems Cybersecurity, and is a Fellow of the Alan Turing Institute, where he is a principal investigator on a $9 million project developing trustworthy digital infrastructure.  Carsten is co-investigator on the Framework for Responsible AI in Finance project, leading on Security and Privacy. He has an international research reputation, having published over 450 peer-reviewed papers, and successfully supervising more than 20 PhD students to completion. He sits on two Royal Society working groups. Carsten is keen to support students in secure and private AI and has access to a number of government and industry contacts to support the relevance and impact of the study.

Julie A. McCann is a Professor of Computer Systems with Imperial College London and has worked in Edge Computing for over 20 years. She is currently interested in the optimisation of AI at the edge for sensing and communications, its explainability, and its security, for many applications. Julie is currently Co-Director of the Imperial School of Convergence Science in Security, Space and Telecoms and Director of the EPSRC/DSIT funded National CHEDDAR Communications Research Hub. She  leads the Adaptive Emergent Systems Engineering Research (AESE) Group and has supervised 30+ PhD students. Julie has acted as Associate Editor and PC member for, and has published extensively in, top tier conferences and journals that cover; self-organizing algorithms and protocols for Wireless and RF (RADAR) Sensor systems, Internet of Things, and Cyber-physical systems.  Between 2015-2022 she was the Deputy Director of the PETRAS IoT Cybersecurity Hub, Critical Ecosystems Lead for the Alan Turing Institute, and Co-I on the EPSRC funded Science for Sensor Systems Software programme grant. Between 2018-2024 NRF funded her lab in Singapore with I2R and HDB. Between 2012-2017 she directed the Intel Collaborative Research Institute (ICRI) for Sustainable Cities. Julie holds the 2018 UKRI Suffrage Science Award for Computing and Mathematics and the 2020 President’s Medal for Research Excellence.

Prof. Shishir Nagaraja is the Chair of Cybersecurity at the School of Computing at Newcastle University where he directs the Network and Distributed Systems Security Lab. He is known for discovering social-malware surveillance. His work made a foundational link between game-theory and complex networks to understand how attack and defense strategies playoff. His research interests are Network Security and Privacy challenges in AI. His work has attracted £14M in funding from various agencies. He is National Skills Lead and Cybersecurity Theme Lead on the Edge AI Hub.

Boguslaw Obara is a Professor of Image Informatics at the School of Computing and Dean of Business, Innovation and Skills at Newcastle University. He is also a Turing Fellow at The Alan Turing Institute. He obtained his master’s in computational physics from Jagiellonian University and a PhD in Image Processing from AGH University of Science and Technology. Before joining Newcastle University as a Professor, he held research assistant positions at the Polish Academy of Sciences and the Computer Vision Laboratory, at ETH Zurich. He was a Fulbright Fellow at the Vision Research Laboratory, held postdoctoral positions at the Center for BioImage Informatics, University of California, and the Oxford e-Research Centre, University of Oxford, and served as an assistant, associate, and professor in the Department of Computer Science at Durham University. Boguslaw Obara was also an AstraZeneca Visiting Professor in Image Processing & Artificial Intelligence. Boguslaw’s research focuses on designing and implementing complex image analysis and processing, pattern recognition, computer vision, and machine learning solutions applied to a wide range of domains.

PhD aspirants in Artificial Intelligence will be working with Dr Varun Ojha, whose research works are seminal in the field of energy and resource-efficient AI. He has pioneering contributions in safe and secure AI. He works closely and collaboratively with his PhD students to produce excellent results for his students. Dr Ojha has a Google Scholar h-index of 15 and 1,471+ citations and has over 70+ top-tier journals and conference publications. Dr Ojha’s research experience spans several prestigious research fellowships such as the Marie-Curie Fellowship, ETH Postdoctoral Fellowship, and DST Fellowship. He is the Artificial Intelligence Theme Leader and Co-I on the EPSRC-funded National Edge AI Hub.      

Prof Savvas Papagiannidis is a Professor of Information Systems, Digital Innovation & Transformation. He is the Head of the Information Systems and Operations Group in Newcastle University Business School and the Research Impact Director at the National Edge AI Hub. His research interests revolve around electronic business and its various sub-domains and how digital technologies can transform organisations and societies alike. More specifically, his research aims to inform our understanding of how e-business technologies affect the social and business environment, organisational strategies and business models, and how these are implemented in terms of functional innovations. His work puts strong emphasis on innovation, new value creation and exploitation of entrepreneurial opportunities, within the context of different industries. 

Omer Rana is Professor of Performance Engineering at Cardiff University School of Computer Science and Informatics, with research interests in distributed computing (especially cloud and edge computing), deployment of machine learning models on edge computing systems and supporting cyber-resilience (combining cybersecurity and systems resilience) on such systems. He has contributed to work in both computer science and to a number of application areas – especially transportation systems, in-vehicle systems and social data science applications. He has supervised 16 PhD students to completion and participated in PhD examinations of over 130+ students (in the UK and Internationally). He holds a PhD in Neural Computing and Parallel Architectures (from Imperial College London), an MSc in Microelectronics systems design (University of Southampton) and a BEng in Information Systems Engineering (from Imperial College London).

Professor Rishad Shafik, Newcastle University

Professor Rishad Shafik holds the title of Personal Chair in Microelectronic Systems Design within the Microsystems Research Group and serves as the Director of the Microsystems AI Lab. He is also a Co-founder of Literal Labs. His research emphasises hardware/software co-design of machine learning systems, with a particular focus on ultra-low-power design using Tsetlin Machines. He has co-edited two books, including “Energy-efficient Fault-Tolerant Systems” published by Springer USA, and has authored or co-authored over 200 research articles in prominent international journals and conference proceedings. Of these, seven were nominated for best paper awards, with some winning best paper or poster awards. He is a Member of the Institute of Engineering and Technology, a Senior Member of IEEE, a Steering Member of the EPSRC-funded eFuturesv3, and a regular contributor to, and organiser of, major conferences. He earned his PhD and MSc (with distinction) degrees from the University of Southampton in 2010 and 2005, respectively, and a BSc in Electronic Engineering (with distinction) from IUT, Bangladesh, in 2001.

Working with Dr Ellis Solaiman at the National Edge AI Hub provides PhD students with a rigorous environment for advancing trust and resilience in distributed systems. A Reader in Computer Science, Senior Fellow of the Higher Education Academy, and Fellow of the British Computer Society, Dr Solaiman’s contributions span AI, blockchain, IoT, and cloud ecosystems. His achievements include over 70 publications, several best paper awards, and key roles on major research projects. He serves as Co-Investigator on the £1m EPSRC project in scalable circular supply chains, and as Data Sensitive Applications Theme Leader on the £12m National Edge AI Hub. Drawing on advanced methods and technologies, his research focuses on developing secure, trusted, reliable architectures that support sustainable digital services across diverse domains. Under his supervision, PhD candidates gain a robust academic foundation and industry-relevant skills. Most of his students are award winning and have progressed to prestigious academic and industrial positions. Dr Solaiman’s mentorship cultivates a new cohort of leaders in cutting-edge distributed computing research.

Dr Tomasz Szydlo is a Senior Lecturer in the School of Computing. He explores the IoT and TinyML research areas and contributes to the open-source with his FogML enablement tools for resource-constrained devices. He cooperated with several research and industrial partners including the Machine Learning and Inference Laboratory at George Mason University, working on the conversion of rules into decision trees, as well as with Samsung and Comarch working on smart systems. He was an intern at IBM Hursley, UK, where he worked on integrating the MQTT protocol with service-oriented device architectures and visiting researcher at IBM TJ Watson. He has participated in several EU and national research projects. Currently he is the TinyML Theme Co-Leader and Co-I on the EPSRC-funded National Edge AI Hub. PhD applications will work with him on systems research for Edge AI.

Dr. Bo Wei has been a senior lecturer (associate professor) in the School of Computing at Newcastle University. He was an assistant professor at Lancaster University and a postdoctoral research assistant at University of Oxford. He obtained his PhD degree in Computer Science and Engineering in 2015 from the University of New South Wales, Australia. His research interests are mobile systems, Internet of Things, Cyber Physical Systems, cyber security and wireless sensor networks. Bo regularly publishes papers in top conferences and journals (Core A*), such as Ubicomp, IPSN, SenSys, as well as IEEE/ACM transactions. Bo is on the editorial board of Ad Hoc Networks Journal and serves as Social Media Chair of CPS-IoT Week 2023. He has also been on technical program committees of more than 16 international conferences, including top-tier conferences, such as IPSN’23, EWSN’22, ECAI’20, MASS’18, etc. Bo was also the session chair of BuildSys’20 and IROS’20. Bo has been a guest editor of several special issues as well.

Dr. Rehmat Ullah is  a Senior Lecturer (Associate Professor) at the School of Computing at Newcastle University, UK. His research focuses on the broader areas of network and distributed systems that span cloud-edge-device continuum and edge intelligence applications. Working with Dr. Rehmat at the National Edge AI Hub provides PhD students with opportunities to engage in cutting edge research in Edge AI and make impactful contributions to this domain. Dr. Rehmat has an established and growing publication record in Network and Distributed Systems, Cloud/Edge Computing and IoT. His research has been published in premier conferences, journals, and patents, including UCC, HotMobile, ACM ICN, IEEE Transactions on Parallel and Distributed Systems, IEEE Transactions on Network Science and Engineering, IEEE Communications Magazine, IEEE Internet of Things journal, IEEE Wireless Communications Magazine, IEEE Network Magazine, Journal of Network and Computer Applications, and Future Generation Computer Systems. He is a named inventor on 8 patent applications (filed in US and South Korea). He has served as a TPC member, keynote speaker, session chair and general chair for several flagship conferences such as ACM ICN 2022, ACM IMC 2018, and ICC 2023/24. 

Blesson Varghese is a Reader in Computer Science at the University of St Andrews. He has held a Royal Society fellowship to British Telecommunications and directs the Edge Computing Hub funded by Rakuten Mobile, Japan. He received the 2021 IEEE Rising Star Award from the Technical Committee on the Internet for fundamental contributions to edge computing systems and applications. Within the UKRI National Edge AI Hub he serves as a research theme co-lead on edge computing for AI. He is interested in developing innovative and practical systems for making edge AI doable on resource-constrained devices. 

Assistant Professor Jennifer Williams, The Alan Turing Institute and University of Southampton

Dr Jennifer Williams is an Assistant Professor in Electronics and Computer Science, and an Associate Scientific Advisor for the Alan Turing Institute BridgeAI programme. Her research explores creation of trustworthy, private, and secure speech/audio solutions with a particular interest in edge devices and ultra-low power solutions. Dr Williams leads a Responsible AI UK International Partnership with the UK, US, and Australia on “AI Regulation Assurance for Safety-Critical Systems” across sectors. She has many years of experience developing speech and language technology in the US, UK, Japan and Singapore both inside and outside of academia. She is a Senior Member of IEEE and a former Chair of the ISCA special interest group on Security and Privacy in Speech Communication (SPSC-SIG). Dr Williams is also an active member of the NIST-OSAC subcommittee on speaker recognition for forensic science where she focuses on standards for deepfakes and synthetic media.

Xianghua Xie (XX) is a Professor at the Department of Computer Science, Swansea University, where he leads the Computer Vision and Machine Leaning group (http://csvision.swan.ac.uk). His research covers various aspects of computer vision and pattern recognition. He was a recipient of an RCUK academic fellowship, and has been an investigator on several projects funded by UKRI, Leverhulme, NISCHR etc. XX has made notable contributions in the areas of Pattern Recognition and Machine Intelligence and their applications to real world problems. Those of significant importance include federated learning, detecting abnormal patterns in complex visual and medical data, assisted diagnosis using automated image analysis, fully automated volumetric image segmentation, registration, and motion analysis, machine understanding of human action, efficient deep learning, and deep learning on irregular domains. He has published over 200 fully refereed research publications and (co-)edited several conference proceedings. He is an associate editor of a number of journals, including Pattern Recognition, and has (co-)chaired a number of conferences, including BMVC 2015&2019.

Next steps

Initially, please get in touch with the most probable supervisors aligned with your research interests. Subsequently, depending on the supervisory team, you will need to apply to their institution accordingly. For further details on doctoral degrees and to get more insights, you may want to visit the links provided below.