Senior​/Research Assistant, Genomics

Senior Research Assistant / Research Assistant
- Genomics

Relation is a sector defining Tech Bio company developing transformational medicines, with technology at our core. Our ambition is to understand human biology in unprecedented ways, discovering therapies to treat some of life’s most devastating diseases. We leverage single-cell multi-omics from patient tissue, functional assays, and machine learning to drive disease understanding, from cause to cure.

We are scaling rapidly and building a team of exceptional individuals to push the boundaries of drug discovery. You will work in highly interdisciplinary teams where biology, computation, and engineering come together to solve complex problems that have not been solved before. Our state-of-the-art wet and dry labs in the heart of London are designed to accelerate this integration and translate insight into impact.

We are committed to building diverse and inclusive teams. Relation is an equal opportunities employer and does not discriminate on the basis of gender, sexual orientation, marital or civil partnership status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability, or age.

By joining Relation, you will help define how medicines are discovered and deliver meaningful impact for patients.

At Relation, we are building proprietary large-scale datasets to advance the prediction of disease-associated genes using cutting‑edge functional genomics and machine learning approaches. We are offering an exciting opportunity for a Senior Research Assistant/ Research Assistant
- Genomics to help expand our capabilities to run large scale perturbation studies with single‑cell Transcriptomic and Epigenomic readouts.

In this role, you will be at the forefront of applying single-cell genomics to large perturbation screens, interfacing with automated platforms for high‑throughput discovery. You will contribute to the single-cell library generation workflow that takes perturbation screens into ML‑ready sequencing data. In this role you will contribute to the running of both droplet microfluidics and combinatorial‑indexing scRNAseq and scATAC‑seq approaches, processing libraries to sequencing, and helping move these protocols from the bench onto our automated platforms.

• Run single-cell RNA‑seq and ATAC‑seq workflows end-to-end from cell input through to sequencing‑ready libraries.
• Process single-cell sequencing libraries through the full preparation to a consistent, QC‑passing standard.
• Partner closely with automation engineers to port manual single-cell and library prep workflows onto automated systems.
• Maintain chain‑of‑custody for genomics samples, plate maps and metadata capture in our LIMS/ELN so every library is unambiguously traceable.
• Interface with the computational and ML teams on library design, demultiplexing logic, expected outputs, and metadata schema.
• Author and maintain SOPs and experimental records in our LIMS/ELN system.
• Monitor day‑to‑day lab activities, maintain reagent stock levels, ensure equipment is properly maintained, and adhere strictly to good lab practice standards.

• A Bachelor's or Master's degree in a relevant Life Sciences discipline with 2+ years of additional experience in Industry or an Academic Genomics Core Facility.
• Hands‑on expertise with single‑cell genomics library generation on droplet microfluidics and/or combinatorial‑indexing methods, experience with scATAC‑seq or other epigenomic methods is a plus.
• Familiarity with NGS operations and library QC, Illumina sequencing essential; experience with Ultima or other platforms a plus.
• Strong cross‑functional coordination skills, with a track record of working effectively alongside computational/ML colleagues.
• A good understanding of the QC, batch‑effect, and experimental‑design considerations that determine whether large‑scale data are usable downstream.
• Knowledge of LIMS/ELN systems (e.g. Benchling) and disciplined metadata and sample‑tracking practice.
• Experience with lab automation and/ or evidence of collaboration experience with automation engineers is desirable but not…