Scientist – Functional Genomics

At Relation we embrace diversity, equality and inclusion and we are committed to building diverse teams.

We are an equal opportunities employer and do not discriminate on the grounds of gender, sexual orientation, marital or civil partner status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability or age.

We strive to create an inclusive interdisciplinary workplace that cultivates innovation through collaboration, empowering and supporting everyone to do their best work and develop to their highest potential.

Overview

The poor understanding of the biology underlying disease remains the critical bottleneck of drug discovery. As a result, we often don’t know why patients become sick while many drug candidates fail in clinical trials. To elucidate the biology of human disease, we use the power of ActiveGraph machine learning (ML), combining graph ML with active learning. An important challenge for any drug discovery company using machine learning is so-called “ground-truth data” or information known to be true.

Relation’s technology generates genomic data from human samples provided by proprietary biobanks to produce direct insights into critical biological relationships that are fed directly into its ML systems.

The platform then requests new experiments from our functional genomics lab to improve its predictive ability, cutting through an otherwise intractable combinatorial space. Relation is pioneering a “Lab-in-the-Loop” that can integrate active learning at every step of drug discovery, from predicting cell states to the validation of new targets.

The Opportunity

Relation has an excellent opportunity for a Scientist to join an interdisciplinary, highly collaborative team of experimental and computational drug discovery researchers in our newly built state-of-the-art functional genomics lab in London.

Large-scale genetic studies, including genome-wide association studies (GWAS), have discovered thousands of variants and loci associated with complex diseases, yet it is difficult to draw disease insight as the vast majority of loci lie in non-coding regions of the genome and have unknown function. At Relation, we are generating proprietary large-scale datasets to accelerate the prediction of disease genes from these loci using state-of-the-art functional genomics and machine learning methods. We will identify the key effector genes, cells and pathways involved in the pathophysiology of disease and proceed to predict disease targets for experimental validation.

We have an exciting opportunity for a talented Scientist to contribute to the cutting-edge drug discovery endeavours of Relation’s experimental laboratory. Aside from major contributions to the design and execution of large-scale functional genomics and molecular biology experiments, the post-holder is expected to contribute to the interpretation of scientific data as well as the upkeep of the lab, to interact with the ML team in project-focused discussions and to stay abreast of new functional genomics and molecular biology methodologies.

By joining Relation, you will be part of an exceptionally talented team, learn a broad range of skills within and outside your area of expertise, help us shape our culture and ultimately, make a positive impact in patients’ lives.

Professionally, you have:

o A PhD in biotech/pharma/academia, with demonstrable experience with CRISPR/Cas9-based large-scale functional genomics approaches (e.g. pooled genome-wide screens, perturb-seq).

o Familiarity with CL2 laboratory environments and handling of lentiviral particles.

o Broad experience with a variety of mammalian cellular models including established cell lines, primary and stem cells.

o A solid background in molecular biology (cloning, PCR, RT-qPCR, western blotting, fluorescence microscopy) and broad experience with the optimisation/development of cellular assays.

o Knowledge of NGS pipelines and single-cell technologies.

o Strong analytical skills and proficiency in interpreting/integrating large-scale datasets.

o A proven ability to deliver to tight timelines.

o Experience with flow cytometry and cell sorting (desirable).

o Computational skills: bioinformatics tools, coding and machine learning (desirable).

Personally, you have:

 A passion for applying large-scale molecular genetics and machine learning approaches to the

problem of identifying disease genes and drug targets.

 Excellent organisation skills, independence, motivation and a proactive attitude.

 An ability to build effective working relationships with proven team-working skills.

 An inclusive attitude and inquisitive nature.

 The ability to communicate effectively with line management, stakeholders and scientists from

multiple disciplines, including computational scientists.

 Excellent attention to detail with the ability to work diligently under pressure.

 A willingness to operate within start-up environments.

To apply for this position please email enquiry@relationrx.com with a cover note and CV.

Application deadline: 13th January 2023

Applications will be reviewed on an ongoing basis and the role may close early if a successful appointment is made.