The Ellison Institute of Technology (EIT) Oxford tackles humanity’s greatest challenges by turning science and technology into impactful global solutions. Focused on areas like health, food security, sustainable agriculture, climate change, clean energy, and AI-driven government innovation, EIT Oxford blends groundbreaking research with practical applications to deliver lasting results.
A cornerstone of EIT Oxford’s mission is its upcoming 300,000-square-foot research facility at the Oxford Science Park, set to open in 2027. This cutting-edge campus will feature advanced labs, an oncology and preventative care clinic, and collaborative spaces to strengthen its partnership with the University of Oxford. It will also host the Ellison Scholars, driving innovation for societal benefit.
The Generative Biology Institute (GBI) at the Ellison Institute of Technology (EIT) Oxford 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 Oxford fosters a culture of collaboration, innovation, and resilience, valuing diverse expertise to drive sustainable solutions to humanity’s enduring challenges.
GBI is looking for a Head of Scientific Compute to shape the future of computational research by leading the development of cutting-edge infrastructure to support high-performance computing, AI-driven analytics, and large-scale data processing.
Working at the intersection of genomics, synthetic biology, and chemistry, you’ll collaborate with researchers and technical teams to design tailored computational solutions, ensuring compliance with data management best practices. You’ll recruit, mentor, and lead a multidisciplinary team while optimising computing resources for scalability and efficiency.

REQUIREMENTS

• A PhD (or equivalent experience) in bioinformatics, or extensive experience of a breadth of software development, architecture and implementation
• Extensive experience in managing scientific computing environments, including expertise in high-performance computing, cloud computing, and large-scale data analytics within a research context.
• Proven track record of leading and managing complex computational projects, ensuring efficiency, scalability, and reproducibility in data analysis workflows.
• Demonstrated ability to build and lead multidisciplinary teams, fostering a culture of innovation, collaboration, and technical excellence.
• Strong technical proficiency in:
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• Programming languages such as Python, Linux

• Cloud computing platforms like AWS, Azure, or Google Cloud, as well as HPC environments.
• Big data management, database design, and distributed computing frameworks.
• Implementation of data security measures and adherence to compliance and regulatory frameworks.
• Exceptional communication skills, capable of engaging with researchers, technical teams, and leadership to maximise the impact of scientific computing initiatives. Extensive experience communicating with non-technical audiences about computing/software

• To lead the development and implementation of a strategic vision for scientific computing, integrating advanced technologies to support large-scale data processing, high-performance computing, and AI-driven analytics in genomic research.
• To oversee and manage the scientific computing infrastructure, ensuring it meets the evolving needs of computational biology, data analysis, and laboratory automation across diverse research programs.
• To collaborate closely with researchers and technical teams to design and implement computational solutions tailored to applications in synthetic biology, chemistry, and genomics.
• To recruit, mentor, and lead a multidisciplinary team, fostering a culture of technical excellence and collaborative research.
• To manage and optimise computing resources, ensuring high availability and scalability to support the institute’s research objectives.
• To establish and enforce best practices for data management and ensure compliance with regulatory and ethical guidelines related to data security, privacy, and reproducibility, particularly in handling extensive biological datasets.
• To strategise with and guide any GBI scientist in realising their scientific computing requirements from conception to implementation and empower and teach scientists to perform scientific computing themselves
• To collaborate with IT and facilities teams to ensure seamless integration of computational infrastructure with laboratory and automation systems, enhancing overall research efficiency.
• To cultivate and manage collaborations with GBI research teams, within EIT more broadly, and with technology providers, and cloud computing services to drive innovation in scientific computing.
• To provide strategic guidance to GBI leadership, advising on future computing needs, emerging technologies, and strategies for digital transformation in scientific research.