Bioinformatics Engineer/Developer

As part of bioXcelerate’s delivery team, you will work closely with experienced statisticians, computational biologists and bioinformatics engineers internally, and may contribute to biotech or pharma client projects as part of a supported delivery team. You will be encouraged to learn from senior colleagues while contributing practical technical capability to high-quality scientific programmes. What you will be doing

• Develop, maintain and improve bioinformatics workflows for genomic and omics datasets, with support from senior team members where appropriate.
• Build reproducible analysis pipelines using workflow tools such as Nextflow, with exposure to WDL, Snakemake or CWL also valuable.
• Analyse population genomics, multi-omics and sequencing datasets using Python, R and bash.
• Contribute to robust, scalable pipelines suitable for HPC or cloud environments including AWS, GCP or Azure.
• Work collaboratively with internal domain experts to deliver reliable analyses that support project decision-making.
• Help prepare client-facing outputs, explain methods and contribute technical input to delivery work under guidance.
• Follow and contribute to best practices for version control, documentation, testing and deployment.
• Support data organisation, quality control and dataset management across projects.

We are seeking a Bioinformatics Engineer / Developer with strong practical bioinformatics, workflow engineering and computational skills to support a variety of data-driven drug discovery projects. This role is suited to someone with a solid foundation in bioinformatics, genomics or computational biology who enjoys building reproducible analyses and scalable workflows., * MSc or equivalent experience in Computer Science, Bioinformatics, Computational Biology, Statistical Genetics or a related field; a PhD is welcome but not required.

• Practical coding skills in Python, R and bash, with an interest in writing clear, maintainable code.
• Experience analysing genomic or omics datasets such as WGS, WES, variant data, RNA-seq or other sequencing data.
• Exposure to workflow development or automation; Nextflow experience is preferred, with WDL, Snakemake or CWL also valuable.
• Familiarity with HPC systems and/or cloud computing environments, or a strong interest in developing these skills.
• Familiarity with version control tools such as Git, and an understanding of good documentation, testing and reproducibility practices.
• Ability to communicate technical concepts clearly to computational and scientific audiences.
• Interest in working with secure research environments, trusted research environments or complex data infrastructures; prior experience is beneficial but not essential.
• Exposure to containerisation tools such as Docker or Singularity would be advantageous.
• Familiarity with population genetics or genomics concepts such as variant QC, population structure or association methods would be beneficial.
• Interest in data engineering approaches, data visualisation, cloud infrastructure-as-code or communicating analytical results clearly.
• Experience working in pharma, biotech or cross-functional scientific teams, including stakeholder or client-facing communication, would be beneficial.

• Competitive base salary.
• Inclusion in our annual discretionary bonus plan with an on-target performance bonus of up to 15%.
• Up to 37 days holiday inclusive of personal and public allocations. Seven are fixed days for Christmas and New Year, and 30 are floating days taken at your discretion, subject to client scheduling and line manager approval.
• Private medical insurance, single cover.
• Group life and income protection insurance.
• Salary sacrifice pension scheme after three months’ employment.

BioXcelerate partners with leading pharma, biotech and academic organisations to accelerate drug discovery through cutting-edge computational methods. We deliver high-impact managed services, data-driven solutions and accelerator products, bringing together expertise across statistical genetics, machine learning, computational biology and bioinformatics engineering.

Our teams make large-scale analyses robust, scalable and actionable, from complex causal inference in health data to modern population genomics and multi-omics pipelines. We work collaboratively with clients and academic partners, embedding skilled scientists directly into discovery teams where needed. The opportunity