relationrx
About Relation Relation is an end-to-end biotech 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 directly from patient tissue, functional assays, and machine learning to drive disease understanding-from cause to cure. This year, we embarked on an exciting dual collaboration with GSK to tackle fibrosis and osteoarthritis, while also advancing our own internal osteoporosis programme. By combining our cutting edge ML capabilities with GSK's 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 impactful therapies 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 reach their highest potential. By joining Relation, you will become 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 This is a unique opportunity for a Senior/Principal Scientist to lead and shape statistical and population genomics efforts to accelerate target identification and validation across multiple therapeutic areas. You will work with large-scale human genetics resources (e.g. biobanks and population cohorts) and apply cutting edge statistical genetics methodologies to generate actionable insights. As part of the Cross Indication team, you will operate at the interface of human genetics, computational biology, and machine learning, translating genetic evidence into target prioritisation frameworks and mechanistic hypotheses. You will play a key role in developing robust, scalable analysis pipelines and ensuring genetic insights are integrated into decision making across the organisation. Your responsibilities Lead statistical and population genomics analyses using large-scale datasets to support target discovery and validation. Design and implement statistical genetics methodologies for target prioritisation, including approaches leveraging GWAS, fine mapping, colocalisation, polygenic risk, rare variant analyses, and functional annotation. Develop scalable computational workflows for reproducible genetics analysis, enabling robust and efficient delivery across multiple programmes. Integrate human genetics evidence with multi omics datasets (e.g. transcriptomics, proteomics) to uncover disease mechanisms and prioritise actionable targets. Partner closely with experimental, translational, and ML teams to validate hypotheses, interpret findings, and guide downstream decision making. Communicate results clearly and confidently to internal stakeholders, including presenting methods, results, risks/limitations, and recommendations. Contribute to publications, scientific communications, and project documentation, supporting scientific excellence and external visibility. Professionally, you have PhD in statistical genetics, genomics, computational biology, bioinformatics, or a related quantitative field. Post PhD experience, ideally including time in an industry, biotech, or pharmaceutical environment. Deep expertise in statistical genetics and population genomics, including experience with large scale human genetic datasets and post GWAS analyses. High proficiency in Python (preferred) and R, with experience working in high performance computing environments. Ability to operate independently at a senior level, providing technical leadership and driving projects from concept through delivery. Desirable knowledge or experiences Familiarity with single cell transcriptomics or patient derived datasets. Experience working in interdisciplinary teams within biotech or pharma settings. Knowledge of machine learning techniques applied to biological data. Experience with causal inference frameworks (e.g. Mendelian randomisation) to strengthen target validation. Strong understanding of the end to end drug discovery process and how genetic evidence informs decision making. Personally, you are Inclusive leader and team player. Clear communicator. Driven by impact. Humble and hungry to learn. Motivated and curious. Impact driven and passionate about improving patient outcomes. Comfortable working in dynamic, fast paced environments. Join us in this exciting role, where your contributions will directly impact advancing our understanding of genetics and disease risk, supporting our mission to deliver transformative medicines to patients. Together, we're not just conducting research-we're setting new standards in the fields of 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.
About Relation Relation is an end-to-end biotech 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 directly from patient tissue, functional assays, and machine learning to drive disease understanding-from cause to cure. This year, we embarked on an exciting dual collaboration with GSK to tackle fibrosis and osteoarthritis, while also advancing our own internal osteoporosis programme. By combining our cutting edge ML capabilities with GSK's 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 impactful therapies 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 reach their highest potential. By joining Relation, you will become 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 This is a unique opportunity for a Senior/Principal Scientist to lead and shape statistical and population genomics efforts to accelerate target identification and validation across multiple therapeutic areas. You will work with large-scale human genetics resources (e.g. biobanks and population cohorts) and apply cutting edge statistical genetics methodologies to generate actionable insights. As part of the Cross Indication team, you will operate at the interface of human genetics, computational biology, and machine learning, translating genetic evidence into target prioritisation frameworks and mechanistic hypotheses. You will play a key role in developing robust, scalable analysis pipelines and ensuring genetic insights are integrated into decision making across the organisation. Your responsibilities Lead statistical and population genomics analyses using large-scale datasets to support target discovery and validation. Design and implement statistical genetics methodologies for target prioritisation, including approaches leveraging GWAS, fine mapping, colocalisation, polygenic risk, rare variant analyses, and functional annotation. Develop scalable computational workflows for reproducible genetics analysis, enabling robust and efficient delivery across multiple programmes. Integrate human genetics evidence with multi omics datasets (e.g. transcriptomics, proteomics) to uncover disease mechanisms and prioritise actionable targets. Partner closely with experimental, translational, and ML teams to validate hypotheses, interpret findings, and guide downstream decision making. Communicate results clearly and confidently to internal stakeholders, including presenting methods, results, risks/limitations, and recommendations. Contribute to publications, scientific communications, and project documentation, supporting scientific excellence and external visibility. Professionally, you have PhD in statistical genetics, genomics, computational biology, bioinformatics, or a related quantitative field. Post PhD experience, ideally including time in an industry, biotech, or pharmaceutical environment. Deep expertise in statistical genetics and population genomics, including experience with large scale human genetic datasets and post GWAS analyses. High proficiency in Python (preferred) and R, with experience working in high performance computing environments. Ability to operate independently at a senior level, providing technical leadership and driving projects from concept through delivery. Desirable knowledge or experiences Familiarity with single cell transcriptomics or patient derived datasets. Experience working in interdisciplinary teams within biotech or pharma settings. Knowledge of machine learning techniques applied to biological data. Experience with causal inference frameworks (e.g. Mendelian randomisation) to strengthen target validation. Strong understanding of the end to end drug discovery process and how genetic evidence informs decision making. Personally, you are Inclusive leader and team player. Clear communicator. Driven by impact. Humble and hungry to learn. Motivated and curious. Impact driven and passionate about improving patient outcomes. Comfortable working in dynamic, fast paced environments. Join us in this exciting role, where your contributions will directly impact advancing our understanding of genetics and disease risk, supporting our mission to deliver transformative medicines to patients. Together, we're not just conducting research-we're setting new standards in the fields of 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.
relationrx
About Relation Relation is an end-to-end biotech 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 directly from patient tissue, functional assays, and machine learning to drive disease understanding-from cause to cure. This year, we embarked on an exciting dual collaboration with GSK to tackle fibrosis and osteoarthritis, while also advancing our own internal osteoporosis programme. By combining our cutting edge ML capabilities with GSK's 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 impactful therapies 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 reach their highest potential. By joining Relation, you will become 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 We are seeking a Principal Data Scientist, Computational Biology to join Relation, working at the intersection of single cell biology, spatial omics, and machine learning. In this role, you will apply advanced computational and statistical approaches to analyse high dimensional biological datasets, generating insights that directly inform disease understanding and drug discovery. You will sit within the Single Cell & Spatial Omics function, working closely with ML researchers, experimental scientists, and software engineers to translate complex biological data into actionable knowledge. This is a highly collaborative, scientifically driven role, suited to someone who enjoys working deeply with data, challenging models with biological insight, and contributing meaningfully to interdisciplinary research programmes. Your responsibilities Analyse and interpret single cell, spatial, and other multi omics datasets to uncover biological mechanisms relevant to disease and therapeutic intervention. Develop and apply statistical and computational methods for transcriptomics and related omics data. Use domain expertise to design rigorous evaluation tasks that test, challenge, and refine ML models. Collaborate closely with ML scientists to inform model assumptions, features, and interpretation. Work with experimental teams to help design experiments and validate computational hypotheses. Clearly communicate insights, results, and methodologies to internal stakeholders and contribute to scientific publications. Professionally, you have A PhD in computational biology, bioinformatics, statistics, physics, mathematics, or a related quantitative field. Strong experience working with high dimensional biological data, including transcriptomics and other omics modalities. Proficiency in Python, with experience in scientific computing and data analysis. A solid understanding of statistical modelling and quantitative methods applied to biological data. Experience with Bayesian models. Desirable knowledge or experiences Hands on experience with single cell and/or spatial omics data, including patient derived samples. Familiarity with machine learning approaches used in biological or biomedical research. Experience working in interdisciplinary teams spanning biology, data science, and ML. Exposure to scalable computing environments. Personally, you are A collaborative, inclusive team player who thrives in interdisciplinary environments. A clear and thoughtful communicator, comfortable explaining complex ideas across disciplines. Curious, impact driven, and motivated by scientific discovery. Humble, open minded, and eager to learn. Passionate about applying data and science to improve patients' lives. Join us in this exciting role where your contributions will have a direct impact on advancing our understanding of genetics and disease risk, supporting our mission to get transformative medicines to patients. Together, we're not just doing research; we're setting new standards in the field of machine learning and genetics. The patient is waiting! Relation Therapeutics is a committed equal opportunities employer. RECRUITMENT AGENCIES: Please note that Relation Therapeutics does not accept unsolicited resumes from agencies. Resumes should not be forwarded to our job aliases or employees. Relation Therapeutics will not be liable for any fees associated with unsolicited CVs.
About Relation Relation is an end-to-end biotech 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 directly from patient tissue, functional assays, and machine learning to drive disease understanding-from cause to cure. This year, we embarked on an exciting dual collaboration with GSK to tackle fibrosis and osteoarthritis, while also advancing our own internal osteoporosis programme. By combining our cutting edge ML capabilities with GSK's 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 impactful therapies 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 reach their highest potential. By joining Relation, you will become 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 We are seeking a Principal Data Scientist, Computational Biology to join Relation, working at the intersection of single cell biology, spatial omics, and machine learning. In this role, you will apply advanced computational and statistical approaches to analyse high dimensional biological datasets, generating insights that directly inform disease understanding and drug discovery. You will sit within the Single Cell & Spatial Omics function, working closely with ML researchers, experimental scientists, and software engineers to translate complex biological data into actionable knowledge. This is a highly collaborative, scientifically driven role, suited to someone who enjoys working deeply with data, challenging models with biological insight, and contributing meaningfully to interdisciplinary research programmes. Your responsibilities Analyse and interpret single cell, spatial, and other multi omics datasets to uncover biological mechanisms relevant to disease and therapeutic intervention. Develop and apply statistical and computational methods for transcriptomics and related omics data. Use domain expertise to design rigorous evaluation tasks that test, challenge, and refine ML models. Collaborate closely with ML scientists to inform model assumptions, features, and interpretation. Work with experimental teams to help design experiments and validate computational hypotheses. Clearly communicate insights, results, and methodologies to internal stakeholders and contribute to scientific publications. Professionally, you have A PhD in computational biology, bioinformatics, statistics, physics, mathematics, or a related quantitative field. Strong experience working with high dimensional biological data, including transcriptomics and other omics modalities. Proficiency in Python, with experience in scientific computing and data analysis. A solid understanding of statistical modelling and quantitative methods applied to biological data. Experience with Bayesian models. Desirable knowledge or experiences Hands on experience with single cell and/or spatial omics data, including patient derived samples. Familiarity with machine learning approaches used in biological or biomedical research. Experience working in interdisciplinary teams spanning biology, data science, and ML. Exposure to scalable computing environments. Personally, you are A collaborative, inclusive team player who thrives in interdisciplinary environments. A clear and thoughtful communicator, comfortable explaining complex ideas across disciplines. Curious, impact driven, and motivated by scientific discovery. Humble, open minded, and eager to learn. Passionate about applying data and science to improve patients' lives. Join us in this exciting role where your contributions will have a direct impact on advancing our understanding of genetics and disease risk, supporting our mission to get transformative medicines to patients. Together, we're not just doing research; we're setting new standards in the field of machine learning and genetics. The patient is waiting! Relation Therapeutics is a committed equal opportunities employer. RECRUITMENT AGENCIES: Please note that Relation Therapeutics does not accept unsolicited resumes from agencies. Resumes should not be forwarded to our job aliases or employees. Relation Therapeutics will not be liable for any fees associated with unsolicited CVs.