practice of commit early and deploy often Preferred qualifications: Experience with Docker or containerized applications, especially architecture of multi-container applications Demonstrated experience with biological or scientific data (e.g. genomics, transcriptomics, proteomics), or pharmaceutical industry experience, especially design of data visualisations Knowledge of agent-based approaches (e.g. LangGraph, PydanticAI, AutoGen More ❯
Terraform and GitHub Actions - essential Agile Methodology Preferred qualifications: Experience with Docker or containerized applications, especially architecture of multi-container applications Demonstrated experience with biological or scientific data (e.g. genomics, transcriptomics, proteomics), or pharmaceutical industry experience Knowledge of AI/ML approaches and deployment of AI/ML powered applications - especially using language models or NLP Experience with Kubernetes and More ❯
Terraform and GitHub Actions - essential Agile Methodology Preferred qualifications: Experience with Docker or containerized applications, especially architecture of multi-container applications Demonstrated experience with biological or scientific data (e.g. genomics, transcriptomics, proteomics), or pharmaceutical industry experience Knowledge of AI/ML approaches and deployment of AI/ML powered applications - especially using language models or NLP Experience with Kubernetes and More ❯
Terraform and GitHub Actions - essential Agile Methodology Preferred qualifications: Experience with Docker or containerized applications, especially architecture of multi-container applications Demonstrated experience with biological or scientific data (e.g. genomics, transcriptomics, proteomics), or pharmaceutical industry experience Knowledge of AI/ML approaches and deployment of AI/ML powered applications - especially using language models or NLP Experience with Kubernetes and More ❯
Terraform and GitHub Actions - essential Agile Methodology Preferred qualifications: Experience with Docker or containerized applications, especially architecture of multi-container applications Demonstrated experience with biological or scientific data (e.g. genomics, transcriptomics, proteomics), or pharmaceutical industry experience Knowledge of AI/ML approaches and deployment of AI/ML powered applications - especially using language models or NLP Experience with Kubernetes and More ❯
GitHub, DevOps tools) with a commitment to early commits and frequent deployments.Preferred Qualifications:Experience with Docker or containerized applications, particularly multi-container architecture.Experience with biological or scientific data (e.g., genomics, transcriptomics, proteomics) or pharmaceutical industry experience, especially in designing data visualisations.Knowledge of agent-based approaches (e.g., LangGraph, PydanticAI, AutoGen).If you're looking for a role where your skills will More ❯
tools) with a commitment to early commits and frequent deployments. Preferred Qualifications: Experience with Docker or containerized applications, particularly multi-container architecture. Experience with biological or scientific data (e.g., genomics, transcriptomics, proteomics) or pharmaceutical industry experience, especially in designing data visualisations. Knowledge of agent-based approaches (e.g., LangGraph, PydanticAI, AutoGen). If you're looking for a role where your More ❯
Strong experience with modern software development tools/ways of working (e.g. git/GitHub, DevOps tools for deployment) Preferred qualifications: Demonstrated experience with biological or scientific data (e.g. genomics, transcriptomics, proteomics), or pharmaceutical industry experience Bioinformatics expertise, familiarity with large scale bioinformatics datasets Experience using Nextflow pipelines Knowledge of NLP techniques and experience of processing unstructured data, using vector More ❯
with unit testing (e.g., pytest) and automated quality checks Understanding of agile software delivery and collaborative development Nice to Have: Experience with bioinformatics or large-scale biological data (e.g., genomics, proteomics) Familiarity with orchestration tools such as Airflow or Google Workflows Experience with containerisation (Docker) Exposure to NLP, unstructured data processing, or vector databases Knowledge of ML and AI-powered More ❯
modern development practices (git/GitHub, CI/CD, agile). Experience with automated testing frameworks such as pytest. Preferred Qualifications Experience working with biological or scientific datasets (e.g. genomics, proteomics, or pharmaceutical data). Knowledge of bioinformatics or large-scale research data. Familiarity with Nextflow, Airflow, or Google Workflows. Understanding of NLP techniques and processing unstructured data. Experience with More ❯
have: Experience with Docker or multi-container application architecture Familiarity with AI/ML technologies such as LLMs, NLP, LangGraph, PydanticAI, or AutoGen Experience with biological or scientific datasets (genomics, proteomics, etc.) Exposure to frontend development (React preferred) Experience benchmarking and improving AI/ML models or agent-based systems What You'll Bring A track record of delivering clean More ❯
value of our unique collection of data and predictions in real-time Automation of end-to-end data flows: Faster and reliable ingestion of high throughput data in genetics, genomics and multi-omics, to extract value of investments in new technology (instrument to analysis-ready data in 12h). - Deliver declarative components for common data ingestion, transformation and publishing techniques More ❯
the value of our unique collection of data and predictions in real-timeAutomation of end-to-end data flows:?Faster and reliable ingestion of high throughput data in genetics, genomics and multi-omics, to extract value of investments in new technology (instrument to analysis-ready data in 12h). - Deliver declarative components for common data ingestion, transformation and publishing techniques More ❯
closely with other parts of the organisation who also are involved in development and maintenance of infrastructure and software, including Programme Teams, Engineering & Enablement, Surveillance Systems, Data Services & Quality, Genomics, Enterprise Architecture and the Development and Operations team. The DD&A team supervises and actively develops solutions and data architecture which meet both our own and wider strategies and design More ❯
