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Hybrid Research Software Engineer, Generative Biology
Posted 3 weeks ago
About the role
- Design and develop high-performance, maintainable, and reusable research software to support large-scale biological and biomedical data analysis.
- Collaborate with researchers to translate scientific requirements into robust computational solutions and production-grade tools.
- Build and optimize AI and scientific data processing pipelines, using modern workflow management systems (e.g., Nextflow, Snakemake, CWL, WDL, etc).
- Implement software engineering best practices, including version control (Git, CI/CD), testing, continuous integration, and documentation.
- Benchmark, profile, and optimize computational workloads for maximum performance, scalability, and efficient use of HPC and cloud environments.
- Work closely with the HPC team to ensure seamless deployment and scaling of applications across on-premise and hybrid infrastructures.
- Support reproducibility and transparency in research through containerization (Singularity, Docker, etc) and workflow orchestration (Nextflow, Kubernetes, OpenHPC, etc).
- Contribute to long-term software and infrastructure strategy in alignment with the Head of Scientific Compute.
- Additional responsibilities at the senior level: Collaborate with GBI staff to research novel compute platforms (e.g. novel ASICs, or Quantum Computers).
- Lead research and development into novel scientific workflow technologies (such as cloud-aware workflow schedulers, scientific data management solutions, quantum algorithms, etc)
- Develop APIs, services, and data interfaces that enable interoperability between systems and research platforms.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Computational Biology, Engineering, or a related field (PhD desirable)
- 3+ years (5+ years at the senior level) of professional experience in software engineering, preferably within a scientific or research environment.
- Ability to work closely with multidisciplinary research teams to deliver computational tools that advance scientific goals.
- Strong communication skills for explaining technical concepts to scientific audiences and non-specialists alike.
- Proven track record of mentoring, collaboration, or technical leadership in research computing projects.
- At the regular level: Experience working with workflow management systems (Nextflow, Snakemake, CWL, or WDL).
- Experience integrating software into HPC or cloud environments (AWS, GCP, Azure, or hybrid systems).
- Understanding of scientific computing, or data science workflows.
- At the senior level: Familiarity with parallel and distributed computing frameworks and techniques (MPI, CUDA, OpenMP, etc).
- Extensive experience working with workflow management systems (Nextflow, Snakemake, CWL, or WDL).
- Experience with bioinformatics, computational biology, scientific computing, or data science workflows.
- At all levels: Proficiency in one or more key programming languages (e.g., Python, Julia, C/C++, Java, or Rust).
- Proven experience developing software for scientific research, data analysis, or computational biology.
- Strong understanding of modern software engineering practices, including CI/CD, testing, and containerization.
Benefits
- Enhanced holiday pay
- Pension
- Life Assurance
- Income Protection
- Private Medical Insurance
- Hospital Cash Plan
- Therapy Services
- Perk Box
- Electrical Car Scheme
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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