Research Software Engineer - Generative Biology Institute at Ellison Institute of Technology
May no longer be active — verify on the employer site
At a glance
- Company
- Ellison Institute of Technology
- Location
- Oxford, United Kingdom
- Work arrangement
- On-site
- Employment type
- Full-time
- Experience
- 2–5 years
- Working hours
- 40 hours
- Visa sponsorship
- Offered, according to the listing
- Posted
✨ The Stack take on this Ellison Institute of Technology job
- 🏢 Ellison Institute of Technology has 6 jobs here, 6 with visa sponsorship see all
- 🛂 Skilled Worker visa. Standard minimum salary: £41,700 a year guide
- 💡 No salary shown. Ask Ellison Institute of Technology if it is above the minimum.
Updated 2026-11-05, from our data and official sources.
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About the role
Responsibilities:
- Design, build and operate software and data systems to support large-scale engineering biology research.
- Develop data collection, ingestion and ETL workflows for sequencing, mass spec and automation platforms.
- Implement cloud-native and HPC infrastructure; containerize workloads and optimize GPU and CPU performance.
- Author reproducible scientific pipelines (Nextflow/Snakemake/CWL/WDL) and integrate with schedulers (Slurm, MPI).
- Build CI/CD, infrastructure-as-code and monitoring for scientific applications to ensure reliability and reproducibility.
- Collaborate with scientists, core facilities and engineers to translate experiments into production-ready systems.
- Maintain code quality, version control and documentation to enable team-wide reuse and auditability.
Requirements:
- Degree in Computer Science, Computational Biology, Engineering or related discipline.
- Proficiency in at least one major language (Python, Julia, Rust, C/C++, Java) and experience in scientific software development.
- Practical experience with cloud platforms (AWS/GCP/Azure), containers (Docker/OCI), orchestration (Kubernetes) and IaC.
- Familiarity with HPC environments, GPU optimization (CUDA/OpenMP), workflow managers and large-scale data engineering.
- Strong problem-solving, communication skills and a commitment to reproducible, well-tested code.
Responsibilities
Design, build, and operate software and data systems to support large-scale biomedical research in engineering biology. This includes developing data collection workflows, cloud-based infrastructure, and optimizing computational workloads on HPC environments.
Requirements
Requires a degree in Computer Science, Computational Biology, or Engineering with proficiency in at least one major programming language. Experience in scientific software development, HPC, and modern software engineering practices is highly desirable.
Key skills
- Python — in 1200 other listings on The Stack
- Julia — in 1 other listing on The Stack
- Rust — in 84 other listings on The Stack
- C/C++ — in 11 other listings on The Stack
- Java — in 360 other listings on The Stack
- Cloud Infrastructure — in 114 other listings on The Stack
- High-Performance Computing — in 3 other listings on The Stack
- Data Engineering — in 120 other listings on The Stack
- CI/CD
- Containerization
- GPU Optimization
- Machine Learning Frameworks
- Workflow Management Systems
- Biomedical Data Analysis
- Software Architecture
- Version Control
On The Stack (as of 2026-11-05)
Frequently asked questions about Ellison Institute of Technology
Is this Research Software Engineer - Generative Biology Institute role still open?
It was posted on 2026-05-22. Listings more than 30 days old may no longer be active, so check Ellison Institute of Technology's site before applying.
Does Ellison Institute of Technology offer visa sponsorship?
This listing is marked as offering visa sponsorship. Eligibility rules are set by the employer, so check the details on Ellison Institute of Technology's site.
Where is this role located?
The listing gives the location as Oxford, United Kingdom. It is marked on-site.
What skills does this role ask for?
The listing names: Python, Julia, Rust, C/C++, Java, Cloud Infrastructure, High-Performance Computing, Data Engineering, CI/CD, Containerization, GPU Optimization, Machine Learning Frameworks, Workflow Management Systems, Biomedical Data Analysis, Software Architecture, Version Control.