Senior Research HPC Engineer (LMS 2914)
Salary £57, 623 - £61,622 plus London Allowance £5,560 per annum
Higher salary of £61,622 - £67,693 plus London Allowance of £5,560 per annum will be available for candidates with significant relevant experience
Permanent | Full Time | Location: Hammersmith London
Main Duties & Approach
Meet regularly with Heads of IT and Bioinformatics, and other parties to develop and deliver Scientific Computing infrastructure, software provisions, and resilient services in line with strategic and scientific goals
Work closely with researchers to develop reusable tools and to translate experimental and analytical requirements into scalable computational solutions that accelerate scientific discovery and improve research productivity
Support researchers in utilising HPC, including triaging user issues and translating common pain points into platform improvements
Help build and maintain reproducible runtime environments, container images, and workflow-supporting services for scientific computing workloads, including bioinformatics, AI/ML, data processing, and simulation workflows
Assume responsibility for coordination and provision of HPC user training and onboarding
Ensure best practices in project management are maintained to ensure work is aligned with defined goals and that HPC projects are managed within agreed benefit, timescale, cost, quality, and risk limits
Monitor, report on, and promote the Institute’s Scientific Computing provisions
Design and manage varied communication strategies for effective and timely stakeholder engagement, including user-group meetings to ensure full visibility of their ongoing and future requirements
Develop and deliver training, documentation (e.g., runbooks, SOPs), and onboarding materials to empower researchers to effectively use computational tools
Maximise opportunities to network with similar organisations to benchmark services and activities Research developing trends to ensure future provision and cost-effective delivery of the Institute’s scientific goals
Technical Activities
Assist with the scoping, provisioning, configuration, scaling, and validation of compute, storage, networking, and platform services within a high-performance computing infrastructure
Support and implement the packaging, versioning, and validation of scientific software to ensure reproducibility and portability across research projects
Establish policies and systems to ensure that workloads placed on the HPC systems are managed, prioritised, and run to achieve optimal service levels and uptime
Install, configure, and manage Linux applications manually and using deployment software
Resolve workflow performance issues on the cluster, and help to design HPC jobs
Implement and maintain management and monitoring tools, report usage levels and service level data
Streamline and automate maintenance, deployment, and configuration tasks
Alongside the Head of IT, assume responsibility for documenting and implementing relevant disaster recovery processes
Ensure awareness via user feedback and monitoring of likely points of failure, proactive maintenance in mitigation, and repair of HPC resources by diagnosing, anticipating, and troubleshooting arising problems
Maintain awareness of emerging HPC software security vulnerabilities and apply relevant security patches
Support the Head of IT in implementing and maintaining HPC related usage policies
Support LMS IT staff as requested for issues and queries relating to standalone Linux/Unix systems
Other duties commensurate with the grade of the post as directed by the supervisor
Person Requirements
Education / Qualifications / Training required (will be assessed from the application form):
Essential
A degree in a computing/scientific research/engineering subject with a significant computational component, or equivalent skills and experience. Significant experience of working at a high-level within a relevant area
Desirable
Industry-standard Linux certifications (e.g. RHCA, RHCSA)
Current qualifications in project management (e.g. PRINCE2)
Knowledge, experience, or qualification in cloud computing
Knowledge or education to a higher level within a scientific field
Knowledge and experience required (will be assessed from the application form and at the interview):
Specific Role Competencies
Essential
Hands-on experience supporting and administering Linux-based systems in an HPC, research, academic, or production environment
Experience in configuration and maintenance of multi-queue job scheduling systems (e.g. SLURM)
Experience in the use of scientific software compilation and deployment systems (e.g. Spack, EasyBuild, Lmod, conda)
Virtualisation and containerisation deployment and management (e.g. Docker, Singularity)
Ability to work closely with multidisciplinary research teams, understand scientific computing needs, and deliver practical services that advance scientific goals
Knowledge of scripting (e.g., Bash) and version control systems (e.g., Git/GitHub) to support reproducible and collaborative research
Integration of heterogeneous Linux/Windows/Mac environments (e.g. Active Directory)
Ability to troubleshoot issues across systems, networking, storage, identity, containers, schedulers, and user workloads, and to follow problems through to a reliable operational fix
Experience with automation tooling (e.g. Salt, xCAT)
Maintain awareness of HPC cyber security principles, best practices, and emerging threats
High attention to detail and accuracy to effectively analyse and interpret complex data and use it solve to complex technical problems quickly and effectively though leadership, delegation and the ability to deep-dive when necessary
Desirable
Exposure to computational research involving GPU, including AI/ML methods applied to biomedical problems
Experience supporting GPU-accelerated workloads, NVIDIA tooling, CUDA-aware environments, and/or AI/ML and bioinformatics workloads on shared compute platforms.
Familiarity with bioinformatics or scientific workflow frameworks (e.g., Nextflow, Snakemake, WDL/Cromwell), and an understanding of reproducible pipeline design
Experience working in a scientific, academic, life-science, or research computing environment where requirements evolve through close collaboration with researchers
Knowledge of tools that support reproducible research and automation (e.g., CI/CD pipelines, workflow testing, IaC tools like Ansible and Terraform)
Familiarity with large-scale biological data types (e.g., from genomics, EM or confocal microscopy, medical imaging, phenomics) and associated storage/access challenges
Familiarity with identity, access, and security controls in Linux or research environments, least-privilege access, and security patching.
Experience of C, R, or Python programming
Experience with GPU-focused hardware and software
Experience monitoring and optimising research workloads and system performance, using tools such as Grafana, Prometheus, Arbiter2
People Leadership
Desirable
Motivating and developing staff to utilise HPC effectively through HPC onboarding and training
Project managing work packages within and between groups
Resolving complaints and in conflict resolution
Personal Skills / Behaviours / Qualities (will be assessed at the interview):
Essential
Excellent verbal and written communication skills
Able to self-motivate when working independently, on projects, and collaboratively within a team
Effectively plans, multitask, and prioritises workload to achieve results, adapting quickly while maintaining control in challenging situations
Ensures appropriate engagement of colleagues with relevant stakeholders and issues
Ability to develop and encourage cross-boundary working relationships and to work collaboratively
Contribute positively to IT and cross-functional teams and shares knowledge and skills
Additional information:
Please upload your CV, the names and contacts of two references, along with a cover letter stating why you are applying for this post (showing evidence against the requirements as per the Job Description and Person Specification). Please quote reference number LMS 2914
Please note that final appointment will be subject to pre-employment screening.
Please note that applications may be reviewed by both LMS and Imperial staff
Closing date: 18 October 2026

