| Location: | Sheffield, Hybrid |
|---|---|
| Salary: | £48,822 to £58,225 |
| Hours: | Full Time |
| Contract Type: | Permanent |
| Placed On: | 7th April 2026 |
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| Closes: | 21st April 2026 |
| Job Ref: | 2351 |
So much of the world impacting research done at the University of Sheffield increasingly relies on computation. From the machine learning and AI models developed by the world class Natural Language Processing Group to the patient specific medical image analysis/modelling pipelines, tackling human diseases, developed by the people in the Insigneo Institute and not forgetting the fundamental science done in our physics and chemistry schools.
Our Research Platforms Engineering team (RPE) is at the heart of enabling computational research across all areas of research. Not only do they ensure that computing platforms are reliable, performant and secure, but they also work with colleagues to identify the future needs of researchers and how advanced computing technology could meet those needs.
We are looking for an exceptional person to lead the RPE team that supports all this research by providing our research computing platforms. These platforms include our current, and planned, High Performance Computer (HPC) with its sizable cluster of CPUs, GPUs, storage arrays and high speed networking as well as our cloud (AWS) based Data Safe Haven, used for researchers working on sensitive data.
As Research Platforms Engineering Lead, you will guide and support the small team of engineers to ensure that the platforms are maintained, supported and developed to continue to meet the needs of our researchers. You will work closely with colleagues across IT services including our infrastructure teams who provide shared capabilities across the University.
You will be expected to have significant knowledge and experience of research computing technologies and applications across both on prem HPC and cloud. These will include cluster management through infrastructure-as-code, high-speed networking, high-performance file systems (e.g. Lustre), managing job schedulers (e.g. Slurm), network and data security, health and availability monitoring and containerisation and virtualisation. Some experience of leading other technical staff and workloads is also expected.
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