Senior Principal Scientist, Biologics AI Innovation

Position: Senior Principal Scientist, AI Innovation – Biologics Engineering
Location: Cambridge, UK
Competitive Salary & Excellent Company Benefits
What you will do
AstraZeneca is seeking an exceptional Senior Principal Scientist to lead innovative Artificial Intelligence (AI) strategies that are transforming its Biologics drug discovery & design. Based at our world-class R&D center in Cambridge, UK, the ideal candidate will spearhead novel computational approaches, drive the design and optimization of Biologics-based therapeutics, and collaborate cross-functionally to deliver scientific and technical breakthroughs at the interface of AI, structural biology, and drug discovery.
Key Responsibilities:
Lead the development and application of advanced AI/ML models for the design, engineering, and optimization of biologics (e.g., monoclonal antibodies, proteins, nanobodies, multispecifics).
Collaborate with multidisciplinary teams to innovate and automate workflows, integrating experimental and computational platforms.
Mentor and guide junior data scientists, bioinformaticians, and molecular engineers in the application of data-driven approaches.
Evaluate emerging technologies and external partnerships relevant to AI-enabled Biologics Engineering.
Lead or contribute to the publication of high-impact scientific articles and present at internal and external conferences.
Establish best practices for integrating large, complex biological datasets (protein sequences, structures, biophysical data) into model development pipelines.
Translate scientific advances into actionable strategies for Biologics program teams, driving impact from hit discovery through candidate optimization.
Champion responsible for innovation in AI, data privacy, and ethical use of machine learning in biologics research.
Essential Requirements
Ph.D. or equivalent in Computational Biology, Structural Biology, Bioinformatics, Computer Science, Engineering, or a related field.
Strong experience in biopharmaceutical R&D or academia, with a strong track record of innovation in AI or machine learning applications for biologics.
Deep expertise in protein modeling, biologics design, or related fields, with hands-on experience deploying deep learning or advanced statistical models in a research environment.
Proficiency with modern AI/ML tools and frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
Demonstrated experience working with large, complex biological and biophysical datasets.
Excellent communication, prioritisation, leadership, and cross-functional collaboration skills.
Strong publication record in peer-reviewed journals and demonstrated impact on biologics drug discovery programs.
Preferred Requirements
Experience leading teams or complex scientific projects in an industrial research setting.
Knowledge of structure-based drug design, antibody engineering, or protein-protein interaction modeling.
Familiarity with laboratory automation, high-throughput screening, and experimental design for biologics discovery.
Awareness of regulatory, ethical, and privacy considerations for data-driven drug discovery.
Why AstraZeneca?
Join us in Cambridge—a vibrant scientific community at the heart of AstraZeneca’s R&D network—to be part of an innovative Biologics Engineering group leveraging AI to shape the future of medicine. We offer a collaborative and inclusive culture, world-class research facilities, and rewarding opportunities to make a global impact.
Interested? Apply now!
Closing date for applications: 8 July 2025
Date Posted
24-Jun-2025

Closing Date
08-Jul-2025 Our mission is to build an inclusive and equitable environment. We want people to feel they belong at AstraZeneca and Alexion, starting with our recruitment process. We welcome and consider applications from all qualified candidates, regardless of characteristics. We offer reasonable adjustments/accommodations to help all candidates to perform at their best. If you have a need for any adjustments/accommodations, please complete the section in the application form.
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