What becomes possible when epigenetics, fragmentomics, and machine learning converge on a brand-new diagnostic platform, and what does it take to lead the science that makes it work?
Tagomics is a Cambridge-based biotechnology company developing a next-generation multi-omic biomarker discovery platform to transform how disease and drug safety are understood, measured, and monitored.
Originating from pioneering research by Dr Robert Neely and colleagues at the University of Birmingham, our proprietary technology integrates genetic, epigenetic, and fragmentomic features from circulating cell-free DNA. Combined with advanced bioinformatics and machine learning, this enables biological insight across applications including early cancer detection, drug safety and organ health monitoring.
With successful proof-of-concept programmes and new funding secured, we are now focused on building towards our first commercial products. To achieve this, we are expanding our multidisciplinary team at Babraham Research Campus, one of Europe's leading life-science hubs.
Read our recent scientific paper:
https://www.cell.com/cell-reports-methods/fulltext/S2667-2375(25)00223-1
The Role
This is the hands-on senior scientific position within our Computational Technology team, reporting to the Director of Computational Technology. You will help set the bioinformatics strategy, lead the analytical programmes that drive our biomarker discovery platform, and translate computational insights into clinically relevant outputs.
It's a role for someone who combines strong technical expertise in NGS and epigenetic analysis with the scientific judgement to shape R&D direction and the communication skills to bring laboratory scientists, engineers, and external partners along with them. You will line manage a small team bioinformaticians, contribute to study design and experimental strategy, and play a meaningful role in how the science evolves as we move towards commercial launch.
The work is truly novel, pushing the boundary of applied science. If you want to apply advanced computational approaches to a platform that doesn't look like anything else in the field, this is a rare opportunity to do that at the right moment.