SYSTRON LAB
Research Software Engineer
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Company Description
The System and Network Interoperability (SYSTRON) Lab, based in the Department of Computer Science at the University of York, UK, advances research in distributed systems, interoperability, and network technologies. Led by Dr. Poonam Yadav, the lab focuses on edge computing performance and resilience, and on connecting diverse systems to address M2M, M2H, and H2D interaction challenges, including protocols and security for future communication systems. SYSTRON operates from the Ian Wand Building on Campus East, with access to specialised facilities such as the SASS lab. The lab also uses the Institute for Safe Autonomy (ISA), a £15 million facility with experimental laboratories for robotics, advanced communications, and quantum technologies. The research team includes PhD students, research associates, and software engineers working collaboratively on cutting-edge projects.
Role Description
The Research Software Engineer will work full time on-site in London, collaborating closely with researchers to design, implement, and evaluate software systems that support SYSTRON Lab’s research agenda. Day-to-day tasks include:
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- Developing and maintaining research prototypes, tools, and frameworks for distributed systems and edge computing
- Integrating software with experimental platforms and testbeds
- Conducting technical investigations, running experiments, analysing performance data, and documenting results in the form of reports, publications, and technical documentation
The role involves:
- Contributing to collaborative project planning
- Participating in regular team meetings
- Supporting the deployment and demonstration of research outcomes
- Mentoring junior team members
- Engaging with external partners when needed
- Ensuring software quality, reproducibility, and maintainability
Qualifications
- Strong foundation in Computer Science, including algorithms, data structures, operating systems, and distributed systems.
- Proficiency in Software Development, with experience in at least one modern programming language (e.g., Python, C/C++, Java) and software engineering best practices.
- Experience in Research, including experimental design, prototyping, and working with academic or industrial research teams.
- Background in Data Science, such as data analysis, statistical methods, or machine learning for evaluating and interpreting experimental results.
- Knowledge of High Performance Computing (HPC), parallel programming, or performance optimisation for compute- and data-intensive applications.
- Familiarity with network protocols, edge/cloud computing platforms, and Linux-based development environments.
- Ability to communicate complex technical concepts clearly in written and spoken English and to collaborate in multidisciplinary teams.
- Relevant degree in Computer Science or a closely related field (e.g., MSc or PhD preferred), or equivalent professional experience.
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