This 12-month industrial placement offers hands-on laboratory experience in biologics engineering, focusing on protein engineering, molecular biology, and cell-based technologies to advance therapies like monoclonal and bispecific antibodies. You'll contribute to drug discovery projects in respiratory, oncology, and immunology, gaining real-world research experience within a supportive, international R&D team.
This role involves leading regulatory strategy and compliance for medicinal products, medical devices, and cosmetics in the UK and Ireland. The specialist will manage submissions, support product launches, ensure compliance with MHRA and HPRA requirements, and maintain regulatory documentation. It requires strong expertise in post-Brexit regulatory pathways and cross-functional collaboration within a dermatology-focused pharmaceutical environment.
Lead the development and execution of translational medicine strategies for oncology programs, integrating AI-driven insights to inform clinical trial design and biomarker development. Collaborate with cross-functional teams to translate preclinical findings into clinical applications and advance companion diagnostics. Play a key role in shaping the scientific direction of early-stage drug development using cutting-edge methodologies and digital biology approaches.
This role involves leading CMC regulatory strategies for international submissions, including IND/CTA/BLA/MAA filings, with a focus on mRNA-based medicines. The individual will guide global regulatory compliance, interact with health authorities, and support quality and manufacturing teams across therapeutic areas like vaccines, oncology, and rare diseases. It requires deep expertise in biologics CMC regulations and a proactive approach to navigating complex regulatory landscapes.
Leads global regulatory strategy for CMC (Chemistry, Manufacturing, and Controls) in support of mRNA-based medicines, ensuring compliance with international regulations and guiding submissions across multiple therapeutic areas. Works closely with manufacturing, quality, and development teams to prepare high-quality regulatory documentation and engage with health authorities. Focuses on biologics, particularly in vaccines, oncology, and rare diseases, within a rapidly expanding biotech environment.
Lead and execute model-informed drug development strategies in oncology, applying advanced pharmacometric and AI/ML techniques to optimize clinical trial design, dose selection, and regulatory submissions. Drive innovation in exposure-response analysis, population PK/PD, and quantitative systems pharmacology within a cross-functional R&D environment.
This 12-month industrial placement offers a laboratory-based role in biopharmaceutical development, working on innovative biologic medicines across therapy areas like oncology and respiratory diseases. You'll apply university knowledge in a collaborative environment using automated workflows, AI tools, and data science to help transform research molecules into life-changing medicines.
Lead and execute model-informed drug development strategies in oncology, applying advanced pharmacometric and AI/ML techniques to optimize dose selection, trial design, and regulatory submissions. Work across multidisciplinary teams to drive quantitative decision-making in clinical pharmacology and contribute to the development of innovative cancer therapies.
Leads global R&D Environmental, Health & Safety (EH&S) programs with a focus on industrial hygiene, exposure risk management, and laboratory safety across Pfizer's research sites. Drives enterprise-wide EH&S standards, governance, and performance metrics while leading a global Community of Practice. Focuses on hazard control for high-potency compounds, engineering controls verification, and AI-enabled EHS improvements.
Leads global Environmental, Health & Safety (EH&S) programs for R&D operations, serving as the principal industrial hygiene expert. Designs exposure assessment and hazard control strategies for high-hazard compounds and laboratories, leads a global EH&S Community of Practice, and aligns enterprise-level safety standards. Drives performance reporting, incident investigations, and AI-enabled improvements across a distributed research network.
Lead the development and execution of bioanalytical strategies for a diverse portfolio of AI-designed therapeutics, including small molecules, biologics, and ADCs. Design and validate PK, PD, and immunogenicity assays, manage global CROs, and integrate bioanalytical data into AI models to refine drug discovery. Play a key role in IND-enabling studies and cross-functional preclinical development in a hybrid London-based role.
A Senior Computational Biologist will drive target discovery in immunology and inflammatory diseases by integrating multi-omics data (phenomics, transcriptomics, genomics, proteomics) to nominate and validate novel therapeutic targets. The role involves developing computational methods, collaborating with cross-functional teams, and translating complex analyses into actionable drug discovery programs using Recursion’s AI-driven platform.
Drive target discovery and validation in precision oncology by integrating multimodal biological data (phenomics, transcriptomics, genomics, proteomics) to identify novel therapeutic targets. Collaborate with cross-functional teams to develop scalable computational methods and build compelling data packages that advance drug programs. Develop criteria for target nomination and support early translational strategies using AI-powered platforms.
Lead the development of an AI scientist platform for drug discovery, combining multimodal biological data and agentic AI to automate target identification and hypothesis generation. Guide a team of data and research scientists in building systems that reason over omics, clinical, and literature data to accelerate pharmaceutical R&D. Work at the intersection of machine learning, computational biology, and pharmaceutical strategy.
This role involves building and scaling the infrastructure that powers an AI-native biological research platform. The engineer will manage Kubernetes clusters, cloud infrastructure, and ML pipelines while ensuring secure, multi-tenant systems with strong isolation. Collaboration with ML, backend, and product teams is central to deploying production systems for AI-driven drug discovery.
