Research Associate in Digital Twins for Transport

1000scholars; Loughborough; On-site; GBP 36,000 - 45,000; Full time

Benefits offered by this job

Flexible working

Hybrid options

Job summary

Loughborough University’s Department of Computer Science invites applications for a Research Associate (SSA Grade 6) to work on the VISION project, a UK Innovate-UK funded initiative. The post focuses on data models, networking frameworks for digital twins, and edge computing for real-time transport and logistics.

You should have or be nearing a PhD in computer science or a related field, with strong knowledge of AI/ML, networking, distributed systems, good programming skills, and a track record

Qualifications

• PhD (or near completion) in CS or related field; strong knowledge of AI/ML, networking, and distributed systems.
• Experience publishing original research in competitive venues; solid coding skills.
• Experience with digital twins, edge computing, IoT or in-network computing is advantageous.

Responsibilities

• Develop data models and a networking framework to connect multiple digital twins.
• Implement edge computing solutions for real-time digital twins in transport and logistics.

Skills

AI/ML knowledge

Computer networking

Distributed systems

Programming skills

Education

PhD (or near completion) in Computer Science

Tools

Python

Job description

This is a full-time, fixed-term post for 12 months, running from 1 January 2027 to 31 December 2027.

The Department of Computer Science at Loughborough University is seeking to appoint a Research Associate (SSA Grade 6) to work on VISION (Virtual Integrated Supply-chain Improvement with Optimized Networking), an international research and development project funded by Innovate UK under the ITEA programme. VISION aims to research and develop a connected, intelligent supply chain management system built around real-time digital twins. Digital twins of vehicles, materials and logistics assets will be connected through common data models so that data, AI models and simulation results can be shared securely across the supply chain, while edge and in-network computing will bring computation close to the data source to support low-latency, real-time operation. The project targets the construction, mining, aerospace and logistics sectors, with the aim of improving efficiency, traceability and resilience and reducing carbon emissions.

The successful candidate will collaborate with Professor Posco Tso, his team, and industrial and academic partners from the UK, Spain, Türkiye and South Korea to develop data models and a networking framework for connecting multiple digital twins, together with edge computing solutions for real-time digital twins in transport and supply chain logistics. They will hold a PhD (or be near completion) in computer science or a related discipline and have sound knowledge of artificial intelligence (AI), machine learning (ML), computer networking and distributed systems, good programming skills, and experience of publishing original research. Research experience in digital twins, edge computing, the Internet of Things or in-network computing, and a strong publication record in competitive venues, would be an advantage.

The Research Associate will be based in the internationally renowned Department of Computer Science at Loughborough University, UK. Founded in 1974, the Department of Computer Science is one of the most well-established university computing departments in the UK with a long track record of developing skilled and highly employable graduates, as well as a reputation for cutting edge research and industry engagement. The University is ranked 8th in the UK (Complete University Guide 2027) and 203rd in the world (QS World University Rankings 2027). In the REF 2021, the department ranked in position 32 out of 90 UK universities, and 91% of Loughborough's research was classed as world-leading or internationally excellent.

Informal enquiries should be made to Professor Posco Tso by email at [e-mail].

For more information refer to the Job Description and Person Specification.

Our Benefits

We’re committed to creating an environment where you can flourish. You’ll enjoy generous time off, including 14 university closure days and bank holidays, plus a holiday purchase scheme. Other benefits include flexible and hybrid working options, family-friendly support, world-class sporting facilities, and a wide range of financial, health, and sustainability perks. Discover more about our full range of rewards and benefits.

From £35,608. Subject to annual pay award.