Senior Computational Genomics Scientist - Pathogen Pathogen Oxford, England, United Kingdom

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 a highly skilled and collaborative (Senior or Non Senior) Scientist with recognised expertise in developing computational methods and algorithms for genomic sequencing data analysis, particularly in the context of genome assembly. This is an exciting opportunity to develop novel computational approaches for microbial data that will become part of our diagnostic products and thus help shape the future of infectious disease diagnostics.

Reporting to the Lead Scientist in Computational Genomics, you will work closely with computational scientists, bioinformaticians, software engineers, and our database and data platform teams to deliver scientifically rigorous, scalable, and clinically relevant innovation in the microbial genomics space.

• Design, develop and evaluate novel computational approaches in areas such as genome assembly, binning, and functional characterisation of genomes from metagenomic sequencing
• Collaborate with scientists across EIT to apply the latest developments in AI/ML to real-world challenges in the pathogen space
• Work with bioinformaticians and software engineers to implement methods in scalable, reproducible, and modular workflows
• Communicate technical concepts to broad audiences and collaborate with interdisciplinary colleagues across the organization
• Perform rigorous benchmarking using public and internal datasets, and guide experimental validation efforts in collaboration with our wet-lab teams

• PhD or equivalent experience in bioinformatics, computational biology, computer science, or a related field
• Senior
  :
  At least 3 years of postdoctoral or industry experience developing computational methods for next-generation sequencing data Non-Senior
  :
  Hands on experience developing computational methods for next-generation sequencing data
• Significant experience with methods for efficient storage, search and assembly of DNA sequences (e.g. hashing, Burrows Wheeler transform, De Bruijn graphs, embeddings and tokenization) and pan genomes
• Proficient in the use of command line interfaces, low and high level programming languages (e.g. Python, Rust) and modern software development techniques (version control, CI/CD)
• Track record of scientific output and engagement with the computational genomics community

• Experience working with microbial genomes and shotgun metagenomics data
• Experience working with long read sequencing data (ONT)
• Experience with bioinformatics workflow frameworks (e.g. Nextflow) and cloud compute environments (e.g. OCI, AWS, GCP)
• Familiarity with Bayesian methods, machine learning, or causal inference in the context of biological data
• Contributions to open source bioinformatics software
• Previous experience mentoring or line managing scientists (
  For Senior
  )

• Strategic thinker with the ability to translate scientific insights into practical solutions
• Effective communicator and enthusiastic knowledge sharer across disciplines
• Rigorous and detail oriented with a commitment to reproducibility and benchmarking
• Comfortable in a fast paced, interdisciplinary environment and able to adapt to evolving priorities
• Collaborative ethos with the ability to work across teams and domains

• Enhanced holiday…