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Ellison Institute of Technology, Oxford Limited

Computational Biologist - Plant Biology Institute

등록일 : 2026-11-06
마감일
2027.01.05(화) 08:59D-60
기관유형
기업
학력
박사
직군
연구원
국가
영국
전공
생명/생물/해양/수산,컴퓨터/통신
근무지
Oxfordshire
근무형태
Permanent
근무시간
Full time
급여액
Salary dependent on experience + travel allowance + bonus
Organization Logo
기관명Ellison Institute of Technology, Oxford Limited
홈페이지https://eit.org/
유형기업

Description

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 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 motivated Computational 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.

Requirements

Essential Skills, Qualifications & Experience:

  • A PhD or equivalent research experience in Computational Biology, Machine Learning, Computer Vision or a related discipline
  • Demonstrated experience independently developing, implementing and evaluating computational methods to address biological questions.
  • Familiarity with at least two different omics types and demonstrated experience in multi-omics integration
  • Experience in applying computer vision methods, including image segmentation and feature extraction, to biological datasets
  • Experience in extracting features from imaging and omics data, and building multi-modal integration pipelines to uncover novel insights.
  • Able to communicate scientific findings clearly and collaborate effectively with experimental scientists, AI researchers and bioinformatics engineers.

Benefits

Our Benefits:

  • Salary dependent on experience + travel allowance + bonus
  • Enhanced holiday + options to buy additional days
  • Pension
  • Life Assurance
  • Income Protection
  • Private Medical Insurance
  • Hospital Cash Plan
  • Therapy Services
  • Perk Box
  • Electric Car Scheme
  • Childcare benefit

Working Together – What It Involves:

  • You must have the right to work permanently in the UK with a willingness to travel as necessary. In certain cases, we can consider sponsorship, and this will be assessed on a case-by-case basis.
  • You will live in, or within easy commuting distance of, Oxford (or be willing to relocate).

접수정보

접수정보는 로그인 후 열람 가능합니다.
채용마감까지 남은 시간
등록일
|
2026-11-06
마감일
|
2027-01-05
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