Join to apply for the Scientist - Functional Genomics role at Relation
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Join to apply for the Scientist - Functional Genomics role at Relation
About Relation
Relation is an end-to-end biotech 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 directly from patient tissue, functional assays, and machine learning to drive disease understanding, from cause to cure.
About Relation
Relation is an end-to-end biotech 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 directly from patient tissue, functional assays, and machine learning to drive disease understanding, from cause to cure.
This year, we’ve embarked on an exciting double collaboration with GSK to tackle fibrosis and osteoarthritis, alongside advancing our own internal osteoporosis programme. By combining our cutting-edge ML capabilities with their deep expertise in drug discovery, this partnership underscores our commitment to pioneering science and delivering impactful therapies to patients.
We are rapidly scaling our technology and discovery teams, offering a unique opportunity to join one of the most innovative TechBio companies. Be part of our dynamic, interdisciplinary teams, collaborating closely to redefine the boundaries of possibility in drug discovery. Our state-of-the-art wet and dry laboratories, located in the heart of London, provide an exceptional environment to foster interdisciplinarity and turn groundbreaking ideas into positive impact for patients.
We are committed to building diverse and inclusive teams. Relation is an equal opportunities employer and does 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 cultivate innovation through collaboration, empowering every team member to do their best work and develop to their highest potential.
By joining Relation, you will be part of an exceptionally talented team, with extraordinary leverage to advance the field of drug discovery. Your work will shape our culture, strategic direction, and, most importantly, impact patients’ lives.
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 identified thousands of variants and loci associated with complex diseases. However, the vast majority of these loci lie in non-coding regions of the genome with unknown functions, making it challenging to draw disease insights. At Relation, we generate proprietary large-scale datasets to accelerate the prediction of disease genes from these loci using state-of-the-art machine learning methods. We identify the key effector genes, cells, and pathways involved in disease pathophysiology to build disease-relevant assays and validate ML platform predictions, identifying candidate targets for further validation.
We have an exciting opportunity for a talented Scientist to contribute intellectually and experimentally to this endeavour. By joining Relation, you will be part of an exceptionally talented team, gain exposure to a broad range of skills beyond your area of expertise, help shape our culture and strategic direction, and ultimately, make a positive impact on patients’ lives.
Professionally, you have
* You are a recent PhD graduate, or up 2 years post PhD working in either a postdoc or industry role.
* Hands-on experience in characterisation and high throughput functional screening assay development.
* At least two years hands-on experience leading the generation of large-scale high quality, screening data in arrayed format, incorporating liquid handling or automation where relevant.
* At least two years of hands-on research experience applying the latest CRISPR/Cas genome-editing approaches, including nucleofection and/or lentiviral transductions.
* A proven ability to deliver to tight timelines.
Desirable Knowledge Or Experiences
* Experience with high content imaging-based high throughput screens and/or FACS-based pooled screens.
* Experience with siRNA, ASO and other interventions for high throughput screening.
* Experience of interdisciplinary team-working, especially with computational scientists.
* Broad expertise in molecular biology including molecular cloning and cell line engineering.
Personally, you have
* A willingness to operate within start-up environments, including delivering to tight timelines, the ability to react to changing priorities or plans, and to help with laboratory operations.
* Excellent attention to detail, analytical, and critical thinking skills
* An ability to build effective working relationships with proven team-working skills
* An ability to communicate effectively with scientists from multiple disciplines
* An inquisitive nature, are self-motivated, and eager to learn
* A desire to work within a fast-paced, data science-first environment.
Join Us
This is an exciting opportunity to be part of a company that is redefining how we understand genetics and disease risk. Your contributions will directly impact the development of transformative medicines for patients. Together, we’re not just conducting research—we’re setting new standards in machine learning and genetics. The patient is waiting.
Relation is a committed equal opportunities employer.
Recruitment Agencies
Please note that Relation does not accept unsolicited resumes from agencies. Resumes should not be forwarded to our job aliases or employees. Relation will not be liable for any fees associated with unsolicited CVs.
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