This role involves leading the development and delivery of strategic life sciences partnerships for the South West Secure Data Environment (SWSDE). Responsibilities include building relationships with life science organizations, developing commercial models, and ensuring governance and ethical standards are maintained.
This role involves hands-on administration, configuration, and continuous improvement of an Electronic Lab Notebook (ELN) platform to support R&D and Technical Development laboratories. The scientist will define ELN standards, design workflows and templates, integrate systems, and develop data repositories to enable data-driven decision-making. Collaboration with cross-functional teams is essential to ensure compliance, data integrity, and effective use of the ELN across scientific operations.
This role involves leading the analytical methodology and evaluation rigor for AI-based workflows within Pfizer's Innovation, Data & Analytics team. The Senior Data Scientist will direct model selection, cohort/segmentation science, and agent decision logic, working closely with engineering and governance teams. The position emphasizes methodological defensibility, cross-functional collaboration, mentorship of junior scientists, and translation of advanced analytics into production-grade AI systems using real-world healthcare data.
This role involves leading the analytical methodology and evaluation rigor for AI-based workflows within Pfizer's Innovation, Data & Analytics team. The Senior Data Scientist (AI Lead) will design model selection frameworks, define cohort and segmentation strategies using real-world healthcare data, and direct the logic behind agentic decision systems. Collaboration with engineering, governance, and data architecture teams is central, along with mentoring junior scientists and driving innovation in AI/ML applications across the pharmaceutical lifecycle.
This role involves building and maintaining scalable data services and platforms that support AI-driven drug discovery. You'll work closely with scientists and ML researchers to ingest, transform, and serve complex scientific data, enabling high-velocity research. The position requires strong backend engineering skills, particularly in Python and GCP, within a collaborative, interdisciplinary environment.
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.
Lead global respiratory epidemiology and real-world evidence initiatives to inform vaccine development, designing and delivering studies on disease burden, treatment patterns, and safety. Partner with cross-functional teams and external collaborators to generate regulatory-grade evidence and shape development strategies. Drive scientific dissemination through publications, regulatory submissions, and international conferences.
Leads global respiratory epidemiology and real-world evidence initiatives to inform vaccine development, designing and delivering studies on disease burden, treatment patterns, and safety. Works cross-functionally with clinical, regulatory, and safety teams, manages external collaborations, and drives scientific dissemination through publications and regulatory submissions. Focuses on strategic epidemiological planning and mentoring junior staff within a matrixed R&D environment.
This role involves applying cutting-edge AI and computational methods to understand disease mechanisms and therapeutic responses. You will integrate multimodal data, develop reusable AI models, and collaborate with cross-functional teams to drive innovation in drug development and translational science.
This role involves designing and executing bioanalytical and immunogenicity strategies to support mRNA-based therapeutic development. The scientist will lead assay development for clinical programmes using platforms like ELISA, MSD, and cell-based methods, ensuring regulatory compliance and robust data generation. The position emphasizes collaboration across multidisciplinary teams and integration of digital tools and AI to advance Moderna's pipeline.
This role involves designing and executing bioanalytical and immunogenicity strategies to support mRNA-based clinical development programmes. The scientist will lead assay development—including ADA, nAb, PK, and PD assays—using platforms like ELISA, MSD, and cell culture, while ensuring regulatory compliance and contributing to Moderna's expanding capabilities in Harwell. The position emphasizes collaboration across multidisciplinary teams and integration of digital and AI-enabled tools to enhance data interpretation and decision-making.
This role involves leading the transformation of regulatory operations globally, driving innovation in regulatory data management, digital platforms, and submissions. The Head of Regulatory Operations will champion cutting-edge technologies like AI and automation to enhance regulatory processes and build a high-performing, inclusive team.
Leads and manages pharmacovigilance safety sciences functions, ensuring compliance with global regulatory standards and overseeing signal detection, safety data analysis, and process optimization. Provides strategic direction for evolving PV legislation and acts as a subject matter expert in audits and inspections. Supports drug development and post-marketing safety reporting while driving data visualization and analytical improvements.
Leads vaccine safety sciences functions, ensuring compliance with pharmacovigilance regulations and global safety standards. Oversees signal detection, safety data analysis, and regulatory documentation while guiding process improvements and cross-functional initiatives. Manages teams and supports regulatory inspections, safety reporting, and the implementation of data visualization tools for enhanced decision-making.
This role involves designing and executing biological screening cascades to validate computational predictions in drug discovery. The scientist will lead biophysical, biochemical, and cellular assay development, collaborate with CROs, and bridge AI-driven insights with experimental validation across oncology and immunology programs. Close collaboration with medicinal chemistry, structural biology, and machine learning teams ensures data informs rational drug design.
