Biologist jobs in United Kingdom

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London (Hybrid - in-person preferred) | Full-time or part-time | £75,000 – £95,000 + equity | Early-stage biotech

Are you a computational scientist passionate about shaping the future of cell reprogramming and longevity biotech? We’re looking for a Senior Bioinformatician to lead our data analysis and computational biology efforts across multi-omics datasets. If you thrive in dynamic environments, love building tools and pipelines, and have a track record of impactful research—we want to hear from you.

You’ll be a key member of our discovery team, helping to interpret complex biological signals and guide experimental design. This is a high-impact opportunity to define bioinformatics strategy and build in-house tools that directly advance our platform.

This role is ideally a full-time in-person or hybrid role at our lab near Kings Cross. We are also open to part-time roles especially if the applicant is in the process of finishing a relevant PhD.

About Us

We’re a VC-backed biotech spun out of a Nobel lab at the University of Cambridge, developing a novel and powerful cell reprogramming mechanism. Our mission is to rejuvenate cells—initially HSCs and T cells for applications in transplantation and cancer immunotherapy. We believe our approach represents a step-change in longevity science, and we’re building a world-class team to realise that potential.

This role will complement our screening and mechanism teams who are developing custom, in-house single-cell sequencing and mass spectrometry methods to gather world-leading and unique data on cellular rejuvenation.

What You’ll Do

1. Lead analysis of multi-omics datasets (ATAC-seq, RNA-seq, single-cell, ChIP-seq, mass spectrometry, etc.)
2. Build, automate, and maintain bioinformatics pipelines and in-house data tools
3. Develop custom analysis scripts, dashboards, or internal apps to support research workflows
4. Work closely with wet-lab scientists to design experiments and interpret data
5. Drive best practices in data storage, versioning, and documentation
6. Collaborate with internal machine learning experts to integrate predictive modelling into pipelines
7. Contribute to strategic decisions across discovery and data infrastructure
8. (Optional) Support library preparation and assist in wet-lab automation development if interested

Minimum Requirements

1. PhD (or equivalent experience) in bioinformatics, computational biology, or a related field - ideally with application in cell reprogramming or immunology
2. First- or early-author publication in genomics, bioinformatics, or a related area
3. Strong experience with omics data types, including bulk and single-cell RNA-seq, ATAC-seq, and ChIP-seq
4. Comfortable with analysis tools like R, Python, Bioconductor, Seurat, Scanpy, etc.
5. Familiarity with cloud data management (GCP), version control (e.g., Git), and storage solutions
6. Knowledge of machine learning concepts, with an eagerness to learn more in-house
7. Excellent communication skills and collaborative mindset
8. Passion for high-quality, reproducible science in a mission-driven environment

Bonus Skills

1. Experience working with mass spec proteomics data
2. Hands-on knowledge of wet-lab methods like library prep or automation (e.g. Opentrons, Hamilton)
3. Prior exposure to cellular reprogramming, longevity or immunology research and datasets
4. Experience developing user-friendly internal tools (e.g., Shiny apps, Streamlit, lightweight dashboards)
5. Familiarity with NGS pipelines, Docker/Nextflow/Snakemake, and secure data practices
6. ELN usage (Benchling) and integration into computational workflows

What We Offer

1. Competitive salary: £75,000–£95,000, based on experience and time commitment
2. Significant equity options in a rapidly growing biotech
3. A collaborative, science-first culture where your work has real impact
4. Flexibility around remote/in-person work, especially for experienced candidates
5. The chance to have impact on foundational technology at the cutting edge of regenerative medicine

Sound like you? Message us or apply directly—we’d love to share more about the science and hear about your experience.

We welcome applicants from all backgrounds and especially encourage applications from early-career scientists who’ve demonstrated excellence. Your impact matters more than your years in industry.