UOS
Redefining in-network computing for compute-native 6G networks
✓ Funded (Competition)
🎓 Artificial Intelligence
🎓 Machine Learning
🎓 Networks
🎓 Systems Engineering
6G networks
DPDK
P4
SmartNICs
XDP
distributed systems
eBPF
edge computing
in-network computing
low-latency systems
network architecture
programmable networking
Fully funded PhD at University of Southampton developing next-generation in-network computing for 6G networks. Focuses on programmable networking, distributed computing, and scalable low-latency architectures for edge-core coordination.
Project Description
This PhD at University of Southampton investigates the future of compute-native 6G networks through in-network computing.
Traditional networks focus on packet forwarding, but next-generation 6G systems will embed computation directly into the data path. This project aims to define the architectural foundations of this shift, enabling distributed computing across edge and core networks.
Key research goals include:
Understanding scalability and performance limits of in-network computing
Designing coordination mechanisms for distributed network functions
Ensuring predictable, secure, and multi-tenant execution of in-network workloads
Developing new abstractions and programming models for network computation
The project combines machine learning, programmable networking, and distributed systems, with hands-on work using modern networking hardware.
Research outputs are expected in top networking venues such as SIGCOMM, NSDI, INFOCOM, and IEEE/ACM Transactions on Networking.
Entry Requirements
Applicants should have:
UK 2:1 degree or equivalent in Computer Science, Electrical Engineering, or related field
Strong programming skills in Python or C/C++
Background in computer networking or mobile networks
Desirable experience:
P4, DPDK, eBPF, XDP
SmartNICs, FPGA, or programmable hardware
Machine learning frameworks
UK 2:1 degree or equivalent in Computer Science, Electrical Engineering, or related field
Strong programming skills in Python or C/C++
Background in computer networking or mobile networks
Desirable experience:
P4, DPDK, eBPF, XDP
SmartNICs, FPGA, or programmable hardware
Machine learning frameworks
How to Apply
Apply via:
University of Southampton PhD application portal
Required:
CV
2 academic references
Transcripts and certificates
English language proof (if required)
Contact:
Dr Aristide Akem – a.t-j.akem@soton.ac.uk
Programme: PhD Computer Science (7089), 2026/27 intake
University of Southampton PhD application portal
Required:
CV
2 academic references
Transcripts and certificates
English language proof (if required)
Contact:
Dr Aristide Akem – a.t-j.akem@soton.ac.uk
Programme: PhD Computer Science (7089), 2026/27 intake
Eligibility
UK/Home
EU
International
Supervisor Profile
DA
Dr Aristide Akem, Prof. Steve Gunn
University of Southampton, School of Electronics & Computer Science (ECS), Faculty of Engineering and Physical Sciences
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