Senior Scientist, Model Systems

Senior Scientist Model Systems

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. Relation is a committed equal opportunities employer.

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 an experienced Senior Scientist to drive our automation capabilities in running large‑scale perturbation studies on mono‑ and co‑culture systems of fibrotic disease.

In this role, you will be at the forefront of scientific discovery and make a meaningful impact in the field of biology, working at the intersection of science and technology within a rapidly growing Tech Bio company. The successful candidate will contribute significantly to capturing the cellular response using a multimodal readout strategy that includes transcriptomics, proteomics and molecular signatures of functional phenotype.

You will partner closely with colleagues across Discovery and Technology while expanding your skills and advancing your knowledge base on assay development, screening and automation.

• Integrate human primary cell lines into robust monoculture and co‑culture models that are capable of large batch production and compatible for high throughput readouts, with the necessary quality control (QC).
• Characterise and optimise multiplexed imaging and biochemical assays that provide readouts for functional phenotyping.
• Transition manually developed perturbation models into an automated arrayed screen.
• Contribute to the development and implementation of new technologies, workflows, and operational infrastructure.
• Carry out data analysis and relevant quality assurance protocols.
• Communicate outcomes of your work to team members and external parties in written or verbal reports.
• Stay up to date with relevant scientific literature and incorporate new findings into research project planning and experiment design.
• Proactively identify potential project issues and communicate proposed solutions to the team.
• Communicate closely with cross‑functional colleagues across biology, machine learning and automation disciplines and assist with solving complex scientific challenges and accelerating programme delivery.

• PhD with 5+ years experience and demonstrable knowledge in assay development and/or target validation.
• Strong background in culturing of primary and immortalised cell lines as well as functional disease‑relevant endpoints with the aim of ensuring required reproducibility and sensitivity in those assays.
• Hands‑on experience in image capture and data interpretation using high‑content imaging with cell painting.
• Scientific knowledge of fibrosis across various tissues.
• Knowledge of CRISPR/Cas9 gene editing for modulating gene expression in 2D and 3D cell systems.
• Prior experience running…