Responsibilities
- Develop and maintain submission and brokering pipelines, including new functionality for spatial transcriptomics and emerging functional genomics technologies.
- Design and implement validation tools for both metadata and file formats of existing and emerging functional genomics assays, contributing to community standards and FAIR data practices.
- Support and enhance internal brokering services for functional genomics submissions, ensuring they remain sustainable and adaptable.
- Develop, maintain, and optimise automated processing pipelines (HPC and Cloud) for harmonisation of functional genomics datasets (bulk RNA-seq, scRNA-seq, spatial assays).
- Contribute to downstream integration into Expression Atlas and related resources, with scope to explore new visualisation or analysis approaches.
- Update data models and outputs to ensure they are AI-ready, interoperable, and reusable.
- Apply modern software engineering best practices, including version control, testing, CI/CD, reproducibility, and containerisation.
- Ensure pipelines and services run reliably in production, with a strong focus on usability and reproducibility for end-users.
- Engage actively with the user community through helpdesk support, training events, and presentations, ensuring tools and services meet their needs.
- Collaborate with curators, developers, and external partners, engage with the user community, and represent the team at international meetings.
We are seeking a highly motivated Bioinformatician to strengthen our submission and analysis pipelines for functional genomics data, with a strong focus on new technologies such as spatial transcriptomics and AI‑ready data formats.
Qualifications
- MSc or PhD in Bioinformatics, Computer Science, or a related field (or equivalent experience).
- Proven experience developing and optimising bioinformatics pipelines.
- Strong experience working in Unix/Linux environments on HPC and/or Cloud platforms with demanding use cases.
- Strong programming skills in at least two of Python, R, Bash, or Perl.
- Proven experience with workflow management systems (e.g. Nextflow or Snakemake).
- Proficiency in Git/GitHub and robust testing strategies.
- Experience with dependency management (containers, Conda).
- Working knowledge of relational databases (SQL and NoSQL) and REST APIs.
- Familiarity with functional genomics data types (bulk RNA-seq, single‑cell RNA-seq; spatial an advantage).
- Excellent communication skills, attention to detail, and ability to deliver high‑quality work to deadlines.
- Experience with data brokering and curation, metadata standards, or ontologies.
- Interest in functional genomics data visualisation or data science.
- Knowledge of DevOps practices, Kubernetes, CI/CD, or software packaging.
- Interest in data visualisation or AI/ML methods for bioinformatics.
- DevOps experience is a plus.
