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Genomics is a science-led transatlantic TechBio company combining large-scale genetic and health data with proprietary analytics to accelerate drug discovery and advance predictive, preventative healthcare. The company operates in two areas: supercharging drug discovery through an AI-enabled advanced genetic analytics platform, and helping people understand their personal risk of common chronic diseases through polygenic risk scores.
You will join a team of experts in human genetics, data science, and software engineering, building the platform at the heart of the Life Sciences work. Your responsibilities will include:
- Expanding and maintaining in-house Life Sciences tools and pipelines, planning your own work and contributing code to a shared codebase alongside Research Engineering team members, Software Engineers, and Data Scientists.
- Implementing algorithms developed within Life Sciences teams to a high standard of robustness, testing, and performance.
- Running high-quality analyses of large-scale biological datasets using existing or bespoke tools, and sharing findings with scientists and other stakeholders.
- Contributing to internal and external presentations and publications arising from the work.
- Keeping knowledge current on innovation and good practice in genomics, data science, and scientific computing.
- At Senior level, leading projects that require integrated updates across multiple tools and coordinating with cross-disciplinary teams to deliver value.
How your time splits across methodology, software engineering, and analysis will reflect your own balance of computational and scientific strengths. This role can be hired at IC2 (Research Engineer) or IC3 (Senior Research Engineer) level depending on experience.
REQUIREMENTS
Essential:
- Strong quantitative background in a scientific field, with ability to explain complex ideas to specialists and non-specialists.
- Skilled at writing high-quality Python code using modern software development practices.
- Confident analysing and learning from large-scale datasets in a scientific context.
- Experienced running tools and workflows in scalable systems (e.g., Linux-based HPC environments or cloud systems).
- Comfortable using LLM programming assistants appropriately within a research software environment.
Desirable:
- Experience working on collaborative codebases using version control and CI/CD.
- Familiarity with common bioinformatics and genomics tools and file formats.
- Experience designing and running large-scale workflows (e.g., WDL, CWL).
- Experience working in remote, cloud-based environments (e.g., AWS).
- Experience creating and working with containers (e.g., Docker, Singularity).
- Additional programming languages, particularly R or C++.
- PhD or postgraduate degree in a scientific field, ideally genomics, bioinformatics, or computational biology, with familiarity in statistics and machine learning.
- Prior experience working in a team, ideally in an industry setting.
