Senior AI Scientist (Machine Cognition)

At AstraZeneca, we pride ourselves on crafting a collaborative culture that champions knowledge-sharing, ambitious thinking and innovation – ultimately providing employees with the opportunity to work across teams, functions and even the globe.

Recognizing the importance of individualized flexibility, our ways of working allow employees to balance personal and work commitments while ensuring we continue to create a strong culture of collaboration and partnership by engaging face-to-face in our offices 3 days a week. Our head office and BlueSky Hub in downtown Toronto are purposely designed with collaboration in mind, providing space where teams can come together to strategize, brainstorm and connect on key projects.

Our dedication to sustainability is also central to our culture and part of what makes AstraZeneca a phenomenal place to work. We know the health of people, the planet and our business are interconnected which is why we’re taking ambitious action to address some of the biggest challenges of our time, from climate change to access to healthcare and disease prevention.

Introduction to role

Are you thrilled by the prospect of developing cognition-inspired AI systems for medical science applications? Do you aspire to build AI solutions that lead the way in treating, modifying, and potentially curing diseases? Would you like to contribute to an iterative, self-improving drug discovery and development framework, applying methods from latent reasoning to evolutionary search? If you thrive in a supportive and inclusive environment, this opportunity might be flawless for you.

Join our pioneering interdisciplinary team at the Centre for Artificial Intelligence, working on the frontier of AI research for Machine Cognition. Your efforts will support the next generation of treatments at the intersection of AI, cognitive science, medicine, and engineering. Your contributions will transform the value chain of therapeutic innovation by uncovering novel biological insights. You will automate processes and streamline decisions. You will improve the pipeline across all therapeutic areas at AstraZeneca. All while pushing the boundaries of intelligence itself!

Accountabilities

• Collaborate efficiently within a team to deliver projects by researching, developing, and applying novel AI methodologies and algorithms. Adhere to engineering guidelines and standard processes for various drug discovery, translational science, preclinical, and clinical applications.
• Participate in a multidisciplinary department dedicated to conceiving, designing, developing, and conducting experiments to test hypotheses, validate new directions, and compare the effectiveness of different AI/ML systems, algorithms, methods, and tools. Focus on discovering, designing, optimizing medicines, and validating them in the clinical domain.
• Provide innovative solutions in research fields such as generative AI, auto-regression, 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.
• 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 more.
• Stay at the forefront of artificial intelligence and machine learning research through journal clubs and seminars. Take part in personal development initiatives. Provide contributions to publications and collaborate with academic and industry teams.

Essential Skills/Experience

• A minimum of MSc, PhD, or equivalent experience is required in machine learning, statistics, computer science, mathematics, physics, or a related technical field. Candidates should have 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.
• Fluent in Python including scientific packages and libraries (e.g. PyTorch TensorFlow Pandas NumPy Matplotlib).
• Ability to communicate and collaborate optimally with diverse individuals and functions reporting and communicating research findings and developments clearly and efficiently to other scientists engineers and domain guides from various fields.

Desirable Skills/Experience

• Research experience shown 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.
• 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 explain-ability in sophisticated models.
• A track record of optimally collaborating with AI engineering teams to deliver sophisticated 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.
• Fundamental research hands-on practical experience and theoretical knowledge of at least two or more 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 multi-modality computational linguistics representation learning foundations of generative modelling computational geometry and geometric methods multi-modal deep learning information retrieval and/or related areas.

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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Date Posted

27-Nov-2025

Closing Date

07-Dec-2025

AstraZeneca embraces diversity and equality of opportunity.  We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills.  We believe that the more inclusive we are, the better our work will be.  We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics.  We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorisation and employment eligibility verification requirements.