Computational Biologist - Plant Biology Institute

Join us at EIT:

At the Ellison Institute of Technology (EIT), we’re on a mission to translate scientific discovery into real world impact. We bring together visionary scientists, technologists, engineers, researchers, educators and innovators to tackle humanity’s greatest challenges in four transformative areas:

• Health, Medical Science & Generative Biology
• Food Security & Sustainable Agriculture
• Climate Change & Managing CO₂
• Artificial Intelligence & Robotics

This is ambitious work - work that demands curiosity, courage, and a relentless drive to make a difference. At EIT, you’ll join a community built on excellence, innovation, tenacity, trust, and collaboration, where bold ideas become real-world breakthroughs. Together, we push boundaries, embrace complexity, and create solutions to scale ideas from lab to society. Explore more at www.eit.org.

Welcome to the Plant Biology Institute:

The Plant Biology Institute, headed by Professor Steve Kelly, is a key part of the Ellison Institute of Technology (EIT) Oxford. The institute aims to develop impactful and commercially sustainable solutions for improving global food production and planetary health through pioneering plant science research.

The Plant Biology Institute will unite world-class researchers who are focused on expanding the frontiers of plant science. Our research is focused on enhancing our ability to feed the planet while simultaneously improving the climate and ecosystem outcomes of food production. By embedding cutting-edge plant science research within an organisation that is focused on solving global challenges at scale, we aim to accelerate the timeline from discovery to global impact.

Areas of exploration include:

• Improved plant productivity, both indoors and outside.
• Reduced reliance on inputs including water, fertilisers, pesticides, and herbicides.
• Novel decarbonised plant-based production platforms for food and medicines.
• Advanced technologies that speed up discovery and deployment in plants.

Researchers will have access to state-of-the-art laboratory and plant growth facilities and have opportunities to collaborate with experts at the forefront of research on AI, automation, and generative biology across the EIT ecosystem. They will also work with global leaders in market development, commercialisation, and impact creation. The Plant Biology Institute has long-term substantial funding to support the unique scale and ambition of its vision.

Your Role:

We are seeking a highly motivatedComputational Biologist to join the Bioinformatics platform team, which builds computational tools for plant biology in close collaboration with the phenotyping platform and research teams.

The successful candidate will work at the intersection of multi-omic analysis and software development, to accelerate plant science research. By developing and implementing robust data analysis pipelines, interactive visualisation tools, and preparing inputs for agentic workflows, your work will directly shape how we make data driven decisions to accelerate plant science research. The role will require working closely with bioinformaticians, research scientists and AI engineers, to design and deliver enterprise-level analytical approaches that meet the evolving needs of the institute.

The ideal candidate will have a strong background in statistics, data analysis and visualization and the ability to translate complex, multi-omic datasets into clear, actionable insights that inform research and decision-making across the institute.

Your Responsibilities:

• Collaborate closely with scientific teams to translate biological questions into computational approaches and develop experimentally testable hypotheses that guide experimental design.
• Prepare multi-omics and imaging datasets for model ingestions, ensuring data quality and consistent annotation across modalities.
• Analyse and integrate omics data sets, including transcriptomics, metabolomics, and proteomics, to inform plant trait engineering strategies.
• Develop computational pipelines for image segmentation, feature extraction and phenotyping across biological scales, including microscopy, growth chamber or in-field data
• Integrate image-derived phenotypes with omics data to link plant traits with molecular signatures and generate biological insights.