Data Scientist Genomic Epidemiology - Pathogen

Ellison Institute of Technology
Oxford
4 days ago
Create job alert

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 Pathogen Mission highlights EIT’s transformative approach, using Whole Genome Sequencing (WGS) and Oracle’s cloud technology to create a global pathogen metagenomics system. This initiative aims to improve diagnostics, provide early epidemic warnings, and guide treatments by profiling antimicrobial resistance. The goal is to deliver certified diagnostic tools for widespread use in labs, hospitals, and public health.


EIT Oxford fosters a culture of collaboration, innovation, and resilience, valuing diverse expertise to drive sustainable solutions to humanity’s enduring challenges.


We are seeking aData Scientist in Genomic Epidemiologyto support the scientific development and implementation of EIT Oxford's Pathogen Programme. Reporting to Head of Population Data Science, the role involves collaborating with internal teams and external partners to assess, develop methods for, and implement at scale, computational and statistical methods for analysing the genomic, phenotypic and epidemiological characteristics of a variety of pathogens in order to inform public health applications ranging from AMR monitoring to outbreak detection and vaccine deployment.


The postholder will carry out research, develop and evaluate high quality software for integration into the EIT Pathogen platform, present findings in peer-reviewed publications and at international forums, contribute to the design and development of large-scale data resources, and explore innovative uses of data to evaluate and improve public health policy and interventions. Ideal candidates will have expertise in high throughput WGS applications within infectious disease epidemiology and monitoring, a strong academic background, excellent skills in research software development, and experience of working with global partners to develop, evaluate and embed new capabilities for data-driven public health.


Key Responsibilities

  • In partnership with the EIT Data and AI team, establish and optimise best practice for managing population-scale genomic and phenotypic data, with appropriate metadata, for downstream analysis.
  • In partnership with the Product and Medical Teams, define use cases for data products and services that generate insights from population-level data on pathogen genotypic and phenotypic diversity for public health applications.
  • Carry out research and development to establish best-in-class analytics for population-scale data science to characterise, analyse and evaluate the potential impact of interventions for applications such as AMR monitoring, outbreak detection, vaccine deployment, community intervention and clinical trials.
  • Deliver high quality software to perform such applications, which can be integrated into the EIT Pathogena Platform by the Technology Team.
  • Present work at international meetings and publish in peer-reviewed journals
  • Work with external partners, where appropriate, to enable knowledge transfer and to support establishment of best practices for genomic and related data analysis using the products and services developed by EIT.

Qualifications & Experience

  • A strong track record of scientific and computational innovation in the field of population-scale infectious disease genomic epidemiology, with an emphasis on public health applications.
  • Up-to-date working knowledge of best practices in research software development and testing.
  • Experience of working with genomic data at a population scale, including the tools and technologies to manage sophisticated analyses.
  • Experience of statistical and/or machine learning methods to make epidemiological inferences from genomic data.
  • Experience of working with partner organisations, including academics, public health workers, and counterparts in partner organisations.

Desirable Knowledge, Skills and Experience

  • Direct experience of working with Oxford Nanopore sequencing technology.

Key Attributes
Scientific and Technical Expertise

  • Proven capability for delivering innovation within public health applications relating to the genomic analysis of infectious disease.
  • Experience in developing the computational tools and technologies to support high volume genomic data analysis for a wide range of users.

Strategic Vision and Leadership

  • Ability to identify opportunities for innovation which align public health needs with commercial objectives and feasibility.
  • Comfortable working within multidisciplinary teams, actively bridging scientific, computational and product expertise.

Collaborative Partnership Builder

  • Experience working with scientific and public health partners in endemic countries to establish and disseminate best practices.

Program Development and Execution

  • Experience of developing new ideas and proposals to develop and validate new tools and technologies.
  • Able to ensure projects are delivered on time and within budget in a delivery-focused setting.

Thought Leadership and Communication

  • Strong academic profile with peer-reviewed publications and a developing network within the genomics community.
  • Skilled at presenting complex ideas at international scientific conferences and contributing to global discourse in genomics.

Benefits

  • Enhanced holiday pay
  • Pension
  • Life Assurance
  • Income Protection
  • Private Medical Insurance
  • Hospital Cash Plan
  • Therapy Services
  • Perk Box
  • Electrical Car Scheme

Why work for EIT

At the Ellison Institute, we believe a collaborative, inclusive team is key to our success. We are building a supportive environment where creative risks are encouraged, and everyone feels heard. Valuing emotional intelligence, empathy, respect, and resilience, we encourage people to be curious and to have a shared commitment to excellence. Join us and make an impact!


Terms of Appointment

You must have the right to work permanently in the UK with a willingness to travel as necessary.


You will live 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

Related Jobs

View all jobs

Data Scientist Genomic Epidemiology - Pathogen

Data Scientist Genomic Epidemiology - Pathogen

Pathogen Genomic Epidemiology Data Scientist

Genomic Epidemiology Data Scientist - Pathogen Platform

Lead Data Scientist - Drug Discovery

Lead Health Data Scientist — Statistical Genetics

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.