Lead clinical pharmacology and modelling & simulation efforts for infectious disease assets, applying pharmacokinetic/pharmacodynamic and exposure-response modelling to inform dose selection, trial design, and regulatory strategy. Work across development phases from early planning to lifecycle management, with a strong emphasis on hands-on quantitative analysis and scientific leadership within a cross-functional environment.
This role involves leading medical oversight in gastrointestinal (GI) oncology clinical development, ensuring patient safety and clinical integrity across study design, execution, and data interpretation. The Medical Director collaborates with cross-functional teams to integrate physician insights into clinical trials, engages with external experts and regulators, and contributes to regulatory submissions and scientific communications. The position requires deep expertise in oncology and clinical development within a global pharmaceutical environment.
This role involves leading material science expertise across the pharmaceutical product lifecycle, focusing on translating material attributes into robust control strategies and manufacturing improvements. The scientist will apply deep technical knowledge to enhance product understanding, support continuous manufacturing platforms, and drive innovation through data-driven insights and digital technologies. Collaboration with global manufacturing sites and cross-functional teams is key to ensuring quality, supply reliability, and scientific excellence.
Lead the development and strategic implementation of AI methodologies for clinical trial design, biomarker discovery, and drug development across AstraZeneca's BioPharmaceuticals pipeline. Drive scientific innovation in collaboration with cross-functional teams, shape regulatory standards for AI in clinical evidence, and represent the company in external scientific forums. Focus on delivering reusable, enterprise-scale AI solutions grounded in rigorous data practices and translational impact.
Develop and optimise cutting-edge AI models at the intersection of machine learning and drug discovery, translating research into scalable, production-ready systems. Work on foundational models like Diffusion networks, Transformers, and GNNs, building robust infrastructure and data pipelines while collaborating closely with scientists. Focus on advancing a digital biology platform to accelerate rational drug design across multiple therapeutic areas.
A Research Scientist focused on applying Large Language Models to drug discovery, working in interdisciplinary teams to develop novel AI-driven approaches for biological and chemical challenges. The role involves advancing LLM techniques such as post-training, reasoning, tool-use, and alignment within a cutting-edge AI research environment. Collaboration with scientists and engineers is central to developing predictive models that accelerate rational drug design.
This role leads the global quality and compliance function for pharmacovigilance (PV) systems, ensuring adherence to international regulations and internal standards across clinical safety, regulatory affairs, and medical affairs. The position combines strategic oversight with hands-on operational leadership, including audit strategy, inspection readiness, deviation and CAPA management, and cross-functional GxP guidance. It requires deep technical expertise in PV processes and strong leadership to drive quality across global teams and third-party vendors.
Leads global pharmacovigilance and regulatory quality assurance, ensuring compliance with GVP, ICH, and regulatory standards across clinical safety, medical affairs, and regulatory affairs. Designs audit strategies, manages inspections, and oversees deviation management, CAPA, and change control systems. Provides cross-functional GxP expertise and drives continuous improvement in PV quality systems.
This role involves leading advanced data science initiatives in drug development, using machine learning, AI, and statistical modeling on clinical and real-world data. The scientist will translate complex business questions into analytical solutions, develop innovative algorithms, and collaborate with internal and external stakeholders to inform decision-making. Work includes hands-on analysis, pipeline development, and methodological innovation using R, Python, and data integration tools.
Lead a global team of statistical programmers, driving standardization, innovation, and quality in clinical trial data analysis. Develop programming strategies using modern tools like R, Git, and AI-enabled technologies, ensuring audit-ready deliverables and alignment with biostatistics and data management. Provide technical leadership and influence global drug development strategy across phases I–IV studies.
This role involves developing and refining bioinformatics workflows to analyse whole genome and metagenomic sequencing data for infectious disease diagnostics. The bioinformatician will work closely with wet lab scientists to interpret complex datasets, focusing on taxonomic classification, antimicrobial resistance prediction, and strain characterisation. The position supports a translational research initiative aiming to deploy scalable diagnostic tools globally.
This role involves conducting advanced research in synthetic evolution, focusing on macromolecular sequence-function relationships and accelerated gene evolution using in vivo systems like OrthoRep. The postdoc will generate large-scale datasets for antibodies and enzymes, explore de novo gene function emergence, and integrate experimental work with machine learning design models. The position emphasizes innovation, collaboration, and translating findings into scalable biological solutions.
This role involves deploying and integrating generative AI models into pharmaceutical and biotech customers' scientific workflows. The engineer will lead end-to-end technical deployments, build production-grade API integrations and data pipelines, and act as a technical liaison between customers and internal research teams. A strong background in ML infrastructure, cloud platforms, and customer-facing delivery in life sciences is essential.
This role involves building and optimizing the machine learning systems that power frontier AI research in life sciences, focusing on distributed training, GPU acceleration, and scalable experiment infrastructure. The engineer will work deeply within the research team to enable rapid iteration on novel biological models using unique, large-scale datasets. The position emphasizes system reliability, performance optimization, and direct impact on scientific discovery through close collaboration with researchers and engineers.
This role involves pioneering research at the intersection of mathematics, machine learning, and biology, focusing on developing novel theoretical frameworks for large-scale foundation models trained on unique metagenomic data. The scientist will lead independent research directions, publish at top venues, and translate mathematical insights into AI models that generate novel biological sequences. The position emphasizes first-principles thinking, collaboration, and real-world impact in therapeutic discovery.
