(Senior) Computational Genomics Scientist - Pathogen

Oxford Source: WhatJobs

£50,000–£70,000

(Senior) Computational Genomics Scientist - Pathogen

At the Ellison Institute of Technology (EIT) Oxford, we are driven by a world‑class faculty of scientists, technologists, policy makers, economists and entrepreneurs, building sustainable solutions to humanity’s most enduring challenges. Our Pathogen Mission uses Whole Genome Sequencing (WGS) and cloud technology to create a global pathogen metagenomics system, improving diagnostics, early epidemic warnings, and antimicrobial resistance profiling.

Job Overview

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, especially genome assembly. This role focuses on novel computational approaches for microbial data – integral to our diagnostic products.

Key Responsibilities

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.

Essential Knowledge, Skills and Experience

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 pangenomes.
Proficiency in 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.

Desirable Knowledge, Skills and Experience

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).

Key Attributes

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.

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 EIT, we believe a collaborative, inclusive team is key to our success. We build a supportive environment where creative risks are encouraged and everyone feels heard. Valuing emotional intelligence, empathy, respect and resilience, we encourage curiosity and a shared commitment to excellence. Join us and make an impact!

Terms of Appointment

Must have the right to work permanently in the UK with a willingness to travel as necessary.
Will live in, or within easy commuting distance of, Oxford.
During peak periods some longer hours and cross‑time‑zone work may be required due to the global nature of the programme.