Publisher
source

Queen Mary University of London

Closing soon

Research Assistant or Postdoctoral Research Associate in Edge AI, Distributed Systems, and Algorithmic Optimization Queen Mary University of London in United Kingdom

Degree Level

Postdoc

Field of study

Computer Science

Funding

Research Assistant or Postdoctoral Research Associate position at Queen Mary University of London; salary and contract details are not specified in the post. The role is a paid academic appointment with competitive salary and standard staff benefits mentioned by the university.

Deadline

Sep 17, 2026

Country flag

Country

United Kingdom

University

Queen Mary University of London

Social connections

How do I apply for this?

Sign in for free to reveal details, requirements, and source links.

Apply for this position

Keywords

Computer Science
Electrical Engineering
Information Technology
Software Engineering
Database Management
Networking
Optimization Algorithm
Distributed System

Suggested positions

About this position

Queen Mary University of London is recruiting a Research Assistant or Postdoctoral Research Associate in the School of Electronic Engineering and Computer Science.

The role focuses on Edge AI, decentralized learning architectures, distributed systems, algorithmic optimization, computer networks, and systems development. The successful candidate will contribute to foundational research, build robust software prototypes, run performance evaluations, and publish results in high-impact academic venues.

This opportunity is aimed at candidates with a background in Computer Science or a related discipline. RA applicants should hold an undergraduate and/or Master’s degree (or equivalent). PDRA applicants must have recently completed, or be close to completing, a PhD in Computer Science or a cognate field. The post also asks for strong research and programming ability, practical experience in distributed AI/ML systems, networked systems, data management, and/or software engineering, plus a publication record in leading peer-reviewed conferences or journals. Open-source experience is considered an advantage.

The position is based at Queen Mary University of London in the United Kingdom. The post is a paid academic appointment with competitive salary and standard staff benefits, including pension, leave, and flexible working arrangements.

Applications must be submitted via the university jobs portal. Candidates are asked to upload documents totalling no more than 10 pages and should not include certificates, references, or research papers at this stage. The deadline is 2026-09-17.

Funding details

Research Assistant or Postdoctoral Research Associate position at Queen Mary University of London; salary and contract details are not specified in the post. The role is a paid academic appointment with competitive salary and standard staff benefits mentioned by the university.

What's required

Applicants should hold an undergraduate and/or Master’s degree in Computer Science or a related discipline. For PDRA level, candidates must have recently completed or be nearing completion of a PhD in Computer Science or a cognate field. Strong expertise in distributed AI/ML systems and computer networks is required, with good practical skills in distributed AI/ML, networked systems, data management, and/or software engineering. Applicants should have a track record of publications in leading peer-reviewed conferences and/or journals in the relevant domains. Experience with broader distributed systems and computer networks, and prior involvement in notable open-source projects, would be advantageous.

How to apply

Apply through the Queen Mary University of London jobs portal using the provided application link. Upload documents totalling no more than 10 pages; do not include certificates, references, or research papers at this stage. Submit before the deadline of 17 Sep 2026.

More information can be found here

Ask ApplyKite AI

Start chatting
Can you summarize this position?
What qualifications are required for this position?
How should I prepare my application?