Lead the development and application of predictive computational models and agentic workflows to evaluate target biology, safety, and translatability in drug discovery. Integrate multimodal biological data and collaborate with cross-functional teams to inform go/no-go decisions. Design and execute hypothesis-driven experiments to validate mechanisms and advance robust, reproducible methods with direct patient impact.
Lead strategic oversight and portfolio analytics for R&D AI and technology investments, providing data-driven insights to senior leadership. Drive decision-making through cross-functional collaboration, governance of the Technology Investment Board, and evaluation of build-vs-buy strategies. Focus on maximizing value, transparency, and delivery confidence across a complex, high-impact portfolio without direct program ownership.
Work as a Clinical Information Scientist on oncology drug development projects, supporting evidence gathering, literature searching, and knowledge management using biomedical databases. Gain hands-on experience in organising and communicating scientific insights to inform decision-making across AstraZeneca’s R&D pipeline.
This 12-month industrial placement offers hands-on experience in synthetic organic chemistry within a pharmaceutical R&D environment. You'll work alongside experienced chemists to design and develop novel synthetic routes for potential drug candidates, using techniques such as purification, reaction monitoring, and automation. The role provides exposure to either medicinal/peptide chemistry in Cambridge or process development in Macclesfield, with opportunities to present work and build key scientific and communication skills.
Provide high-level administrative and operational support to senior leadership, managing complex calendars, coordinating cross-functional initiatives, and ensuring seamless communication across global teams. Play a key role in streamlining processes and maintaining confidentiality in a fast-paced, innovative biotech environment driven by AI-powered drug discovery.
The role involves end-to-end management of clinical trials within a fast-paced, AI-driven drug discovery environment. The Senior Clinical Trial Manager will lead cross-functional teams, oversee trial start-up through close-out, ensure compliance with ICH/GCP standards, and integrate AI innovations into clinical operations. Key responsibilities include vendor and budget management, clinical documentation, data oversight, and supporting regulatory readiness and audits.
Leads external innovation sourcing and evaluation in Haematology, identifying preclinical to Phase 1 assets, driving due diligence, and shaping early partnering strategies. Works within the Therapeutic Area Leadership Team to advance high-potential opportunities and collaborates with Business Development to execute deals. Engages with biotech, academia, and investors to build a robust pipeline.
Leads strategic sourcing and evaluation of early-stage innovation in haematology, from preclinical to Phase 1 assets. Drives due diligence, shapes partnering strategies, and executes transactions in collaboration with Business Development. Embedded in the Therapeutic Area Leadership Team to influence portfolio planning and external innovation priorities.
This role involves monitoring and enhancing security across endpoints, cloud platforms, and networks, with a focus on detection engineering, incident response, and threat intelligence. The engineer will develop detection rules, respond to security incidents, and collaborate with IT and research teams to integrate security into scientific workflows. Work includes tuning SIEM and EDR tools, managing vulnerabilities, and improving security posture in a high-stakes research environment.
This role involves designing and executing high-throughput genome engineering experiments and scalable phenotypic measurements in bacterial systems to generate training data for multi-modal biological models. The researcher will work at the intersection of wet-lab biology and AI, collaborating closely with computational scientists to build and validate models. The position emphasizes method development, data generation, cross-disciplinary collaboration, and mentorship within a cutting-edge synthetic biology institute.
This role involves conducting in-depth clinical data review and trend analysis across all phases of clinical studies to ensure data integrity, scientific plausibility, and patient safety. The Clinical Scientific Expert identifies data insights, supports database lock activities, and contributes to regulatory documentation and safety monitoring. They collaborate with cross-functional teams to enhance data quality processes and support study execution within a hybrid working environment.
Manages regulatory maintenance for a high-complexity pharmaceutical portfolio, ensuring compliance and timely submissions. Develops strategic regulatory input for safety reports, variations, and renewals, while acting as a liaison with health authorities. Supports global approval processes and contributes to process improvements and team mentorship.
The FP&A Manager will lead financial planning and analysis for clinical trials and R&D projects, providing strategic business partnering to scientific and operational teams. This role involves driving financial governance, forecasting, and the automation of reporting processes within a growing biotech environment. The individual will play a key part in scaling financial operations to support OMass’s pipeline in rare diseases and immunology.
A Senior Bioinformatics Scientist will define data requirements for AI models, design biologically sound datasets and evaluations, and ensure data integrity in training foundational genomic models. The role involves close collaboration with deep learning and engineering teams to validate model performance and biological relevance. Work focuses on sequence analysis, annotation, and evolutionary-scale data interpretation to support therapeutic discovery.
This role involves transforming large-scale, complex biological data—primarily microbiomes—into annotated, model-ready resources for AI-driven discovery. The scientist will develop novel methods to analyse non-standard genomic data, ensure data integrity, and contribute to tools that guide global biodiversity sampling. Work spans prokaryotes and eukaryotes, with a focus on innovation where traditional tools fall short.
