Senior Scientist, Biotechnology - Pathogen Pathogen England, United Kingdom

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 .org.

Within this ecosystem, the Pathogen Project exemplifies EIT’s dedication to ground-breaking science. It seeks to transform pathogen risk management, detection and response by leveraging Whole Genome Sequencing (WGS)-based metagenomic and pathogen-specific analytical tools. The goal is to power metagenomic devices using long-read sequencing technologies by building a comprehensive database of pathogen information to inform response. Enabled by Oracle Inc.’s cloud-computing scale and security, the Pathogen Project is advancing toward certified diagnostic tools for deployment in laboratories, hospitals, and public health organisations worldwide.

At EIT, we’re seeking an experienced and detail‑orientated Senior Scientist, Biotechnology, to contribute to the early‑stage development of a device‑based metagenomic pathogen detection platform within EIT Oxford’s Pathogen Programme. This work focuses on establishing proof of concept for a modular workflow enabling infectious disease diagnosis at or near the point of care. In this laboratory‑based role, you will design and execute hypothesis‑led experiments to interrogate and iteratively refine nucleic acid extraction, purification, and manipulation workflows within a fluidic device architecture.

You will apply quantitative characterisation, controlled comparisons, and mechanistic insight to drive system‑level improvements and systematically reduce technical uncertainty through disciplined, evidence‑based experimentation.

You will bring strong expertise and demonstrable experience developing nucleic acid handling or enzyme‑based systems. Experience with surface chemistry, microfluidic environments, polymer or material interfaces, or low‑input nucleic acid workflows is advantageous. You should be comfortable operating in an exploratory, data‑driven research environment, using structured experimentation, quantitative analysis, and rapid, evidence‑guided iteration to navigate ambiguity and progress early‑stage technology development.

• Designing and executing statistically robust, hypothesis-driven experiments with appropriate controls to isolate key variables and generate reproducible, decision‑informing data.
• Applying structured experimental design approaches (e.g. factorial design, parameter sweeps, sensitivity analysis) to systematically explore design space and identify critical performance drivers.
• Investigating the physicochemical principles underlying nucleic acid adsorption, elution, surface interactions, and partitioning within device materials and reagent systems.
• Characterising enzyme–substrate interactions under non‑ideal conditions, including the effects of inhibitors, ionic strength, crowding, and surface chemistry on catalytic efficiency and fidelity.
• Developing and applying quantitative analytical frameworks to define performance metrics, establish baselines, and guide iterative optimisation across workflow stages.
• Systematically identifying sources of variability and technical risk, quantifying their impact, and prioritising mitigation strategies based on experimental evidence and expected effect size.
• Translating mechanistic findings into clear design recommendations that inform workflow architecture, reagent formats, surface treatments, and fluid handling strategies…