Are you excited by the idea of creating cognition-inspired AI systems for medical science application? Do you hope to build the AI Scientists at the forefront of treating, modifying, and even curing disease? Would you like to work on developing an iterative, self-improving drug discovery and development framework, while drawing on methods across various fields, from latent reasoning to evolutionary search? Do you thrive working in a supportive, inclusive environment? If yes, this opportunity may be for you.

Join our pioneering interdisciplinary team working on the frontier of AI research for Machine Cognition, within the Centre for Artificial Intelligence. Your work will support the next generation of treatments at the intersection of AI, cognitive science, medicine and engineering. Your work will contribute to transforming the drug discovery and development value chain, uncovering novel biological insights, automating processes, streamlining decisions, and improving the pipeline across all therapeutic areas at AstraZeneca. All while pushing the frontier of intelligence itself.

Accountabilities:

• You will work efficiently in a team to deliver projects, researching, developing and using novel AI methodologies, and algorithms. Adhering to engineering best practices and standard processes for various drug discovery, translational science, preclinical and clinical applications.
• You will be part of and lead multifunctional projects to conceive, design, develop and conduct experiments to test hypotheses, validate new approaches, and compare the effectiveness of different AI/ML systems, algorithms, methods and tools. Objectives for new applications will focus on the discovery, design, and optimisation of medicines, and their validation in the clinical domain.
• You will provide innovative solutions touching on fields of research such as generative AI, autoregression, diffusion and flow matching methods, reasoning, cognitive analysis of AI, planning, philosophy of science, alignment, deep learning, representation learning, reinforcement learning, meta-learning, active and adaptive learning approaches applied to target ID, assay design and development, lead discovery, lead optimization, in-silico discovery, mechanism of action elucidation, genetic engineering, translational sciences, biomarker discovery evaluation and validation, clinical research, clinical trial support and many other areas.
• You will develop autonomous agentic modules and larger multi-agent systems designed for open-ended scientific exploration, using tools, long and short-term memory, behavior modulation and modification, abstractive propositional confidence, and much more.
• You will remain at the forefront of AI/ML research by participating in journal clubs, seminars, mentoring, and personal development initiatives and contributing to publications and academic and industry collaborations.

Essential Skills/Experience:

• A PhD in machine learning, statistics, computer science, mathematics, physics, or a related technical discipline with relevant fundamental research experience in artificial intelligence and machine learning or equivalent practical experience.
• Theoretical understanding, combined with a strong quantitative knowledge of algebra, algorithms, probability, and statistics, as well as hands-on experimentation analysis, visualisation and observability.
• Experience in theoretical, fundamental AI research and practical aspects of AI/ML foundations and model design, such as improving model efficiency, quantisation, conditional computation, reducing bias, or achieving explainability in complex models.
• Experience in exploiting the simplest tricks to the latest research methods to advance AI/ML capabilities while implementing them in an elegant, stable, and scalable way.
• Fluent in Python, including scientific packages and libraries (e.g. PyTorch, TensorFlow, Pandas, NumPy, Matplotlib).
• Ability to communicate and collaborate effectively with diverse individuals and functions, reporting and presenting research findings and developments clearly and efficiently to other scientists, engineers, and domain experts from various disciplines.
• Fundamental research, hands-on practical experience and deep theoretical knowledge of at least three of the following research areas: multi-agent systems, logic, causal inference, Bayesian optimisation, experimental design, deep learning, reinforcement learning, non-convex optimisation, Bayesian non-parametric, natural language processing, approximate inference, control theory, meta-learning, category theory, statistical mechanics, information theory, knowledge representation, unsupervised, supervised, semi-supervised learning, computational complexity, search and optimisation, artificial neural networks, multi-scale modelling, transfer learning, mathematical optimisation and simulation, planning and control modelling, time series foundation models, federated learning, game theory, statistical inference, pattern recognition, large language models, probability theory, probabilistic programming, Bayesian statistics, applied mathematics, multimodality, computational linguistics, representation learning, foundations of generative modelling, computational geometry and geometric methods, multi-modal deep learning, information retrieval and/or related areas.

Desirable Skills/Experience:

• Research experience demonstrated by journal and conference publications in prestigious venues (with at least one publication as a leading author). Examples include but are not limited to NeurIPS, ICML, ICLR and JMLR.
• A track record of successfully collaborating with AI engineering teams to deliver complex machine learning models and production-ready data and analytics products.
• Practical ability to work on cloud computing environments like AWS, GCP, and Azure.
• Evidence of open-source projects, patents, personal portfolios, products, peer-reviewed publications, or similar track records.

Great People want to Work with us! Find out why:

• GTAA Top Employer Award for 11 years
• Top 100 Employers Award
• Canada’s Most Admired Corporate Culture
• Learn more about working with us in Canada
• View our YouTube channel

Are you interested in working at AZ, apply today!

AstraZeneca is an equal opportunity employer that is committed to diversity and inclusion and providing a workplace that is free from discrimination. AstraZeneca is committed to accommodating persons with disabilities. Such accommodation is available on request in respect of all aspects of the recruitment, assessment and selection process and may be requested by emailing AZCHumanResources@astrazeneca.com.

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