Research Software Engineers

Overview Research Software Engineers (All Levels) - Generative Biology Institute Led by a world-class faculty of scientists, technologists, policy makers, economists and entrepreneurs, the Ellison Institute of Technology aims to develop and deploy commercially sustainable solutions to solve some of humanity's most enduring challenges. Our work is guided by four Humane Endeavours: Health, Medical Science & Generative Biology, Food Security & Sustainable Agriculture, Climate Change & Managing Atmospheric CO2 and Artificial Intelligence & Robotics. Set for completion in 2027, the EIT Campus in Littlemore will include more than 300,000 sq ft of research laboratories, educational and gathering spaces. Fuelled by growing ambition and the strength of Oxford's science ecosystem, EIT is now expanding its footprint to a 2 million sq ft Campus across the western part of The Oxford Science Park. Designed by Foster + Partners led by Lord Norman Foster, this will become a transformative workplace for up to 7,000 people, with autonomous laboratories, purpose-built laboratories including a plant sciences building and dynamic spaces to spark interdisciplinary collaboration. The Generative Biology Institute (GBI) at the Ellison Institute of Technology (EIT) aims to overcome two major challenges in making biology engineerable: 1) the ability to precisely synthesize entire genomes, and 2) understanding which DNA sequences will create biological systems that perform desired functions. Solving these challenges will unlock the potential of biology for transformative solutions in health, sustainability, agriculture, and more. GBI will house 30 groups and over 300 researchers, supported by cutting-edge facilities and sustained funding to address global challenges and advance biology engineering. EIT fosters a culture of collaboration, innovation, and resilience, valuing diverse expertise to drive sustainable solutions to humanity's enduring challenges. Key Responsibilities 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 Senior level responsibilities At the senior level, lead research and development of novel HPC-capable scientific research software such as new approaches to scientific computing, or the integration of novel compute platforms (including novel ASICs and Quantum Computers) into research workflows at GBI. Additional responsibilities at the senior level include collaborating with GBI staff to research novel compute platforms (e.g. novel ASICs, or Quantum Computers), leading research into novel scientific workflow technologies (such as cloud-aware workflow schedulers, scientific data management solutions, quantum algorithms, etc), and developing APIs, services, and data interfaces that enable interoperability between systems and research platforms. Requirements Essential Knowledge, Skills and Experience 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 Technical Expertise 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) Experience integrating software into both HPC and cloud environments (AWS, GCP, Azure, or hybrid systems) 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 Terms of Appointment Applicants must have the right to work in the United Kingdom. Due to the highly specialized technical nature of the role, exceptional international applicants may be considered for sponsorship where appropriate You must be based in, or within easy commuting distance of, Oxford During peak periods, some longer hours may be required and some working across multiple time zones due to the global nature of the programme. #J-18808-Ljbffr