Genomics

HQ
Oxford
Total Offices: 3
164 Total Employees
Year Founded: 2014

Jobs at Genomics

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Recently posted jobs

13 Days AgoSaved
Hybrid
2 Locations
Biotech
Lead reliability, performance, security and integrity of a petabyte-scale analytical data platform. Architect and operate multi-tenant ClickHouse/OLAP clusters, own SLOs, observability, capacity planning, incident response, Data-as-a-Service productisation, agent-ready data access, and multi-tenant security. Line-manage and mentor a small engineering team while remaining hands-on and setting technical direction.
16 Days AgoSaved
Hybrid
2 Locations
Biotech
The Scientist drives innovation in genomic analytics, focusing on polygenic risk scores and targeted therapeutics, utilizing statistical techniques for data analysis.
16 Days AgoSaved
Hybrid
2 Locations
Biotech
As a Senior Scientist, you will innovate and develop methods for Polygenic Risk Scores using genomic and clinical data, applying statistical techniques and leading projects within the team.
18 Days AgoSaved
In-Office
London, Greater London, England, GBR
Biotech
Provide high-level administrative support to multiple senior leaders: manage complex diaries, schedule meetings and offsites, coordinate national/international travel (including visas), process expenses, handle confidential information, and liaise with internal and external stakeholders to ensure seamless leadership operations.
20 Days AgoSaved
Hybrid
2 Locations
Biotech
The Business Development Lead will drive growth in pharma and biotech by developing relationships, managing sales opportunities, and ensuring pipeline accuracy. They will collaborate internally, understand client needs, and bring market insights to the team.
20 Days AgoSaved
Hybrid
2 Locations
Biotech
Lead business development in the life sciences market, engaging with senior execs in pharma/biotech, building client relationships, and driving complex sales.
23 Days AgoSaved
Hybrid
2 Locations
Biotech
Ingest, transform, harmonise and quality-control large genomic datasets (GWAS, genotypes, phenotypes). Configure pipelines, interpret QC diagnostics, investigate anomalies, curate metadata, and collaborate with engineering and science teams to expand genomic data resources and schemas.