AI Research Scientist

Locations: Cambridge, USA (3 days in office, 2 days remote)

What if your AI research could help transform not only how medicines are discovered, but how they reach patients?

Drug discovery has benefited enormously from advances in artificial intelligence. Yet clinical development, one of the most consequential stages in bringing new treatments to patients, remains an extraordinary opportunity for innovation.

Within AstraZeneca’s AI for Clinical Development team, we are reimagining that journey. Our ambition is to use AI, machine learning, statistics, and computational science to help bring safe and effective treatments to patients faster, more efficiently, and with less burden on those participating in clinical research.

We are looking for a Senior Scientist, AI for Oncology Clinical Development who can combine outstanding machine learning expertise with the curiosity and drive to solve complex, high-impact scientific problems.

As a technical contributor, you will work in cross-functional, matrixed teams to address some of AstraZeneca’s most important clinical development questions.

You will have the opportunity to:

• Lead the technical delivery of complex, high-stakes AI initiatives.
• Evaluate and develop advanced AI methods across problem definition, data strategy, governance, algorithm development, validation, and adoption.
• Create and validate novel AI solutions for clinical study design, execution, strategy, and decision-making.
• Apply data, models, and insights across cancer biology and multiple drug modalities.
• Collaborate across key Oncology areas, including hematology, cell therapy, antibody-drug conjugates, small molecules, and biologics.
• Build external collaborations with academic institutions, technology partners, and industry consortia.
• Represent AstraZeneca at scientific conferences, standards bodies, and peer-reviewed venues.
• Contribute first-author research to leading machine learning and clinical AI journals.
• Help shape and share technical knowledge, standards, and effective practices across the team.

This is an opportunity to invent new approaches and then see them applied to real clinical-development challenges, with the potential to measurably advance AstraZeneca’s late-stage Oncology pipeline.

You will have:

• A PhD in a quantitative discipline such as computer science, mathematics, physics, biophysics, bioinformatics, computational biology, computational neuroscience, or biostatistics.
• Exceptional software-development and coding skills, including experience using frontier coding-agent frameworks.
• A deep understanding of machine learning fundamentals.
• Strong expertise in one or more of the following areas: Training and tuning foundation models Bayesian inference Temporal modelling Reinforcement learning Multimodal integration and modelling Model calibration and domain adaptation Data-centric AI, including dataset creation, curation, post-training, benchmarking, and evaluation Model and data evaluation Model interpretability Model post-training and alignment Multi-agent systems and agent harnesses

Your application will be strengthened by experience in one or more of the following:

• Biology or biomedical research.
• Applying machine learning to molecular data, including DNA, RNA, or proteins.
• Working with imaging data such as radiology or microscopy.
• Working with clinical text, electronic health records, or clinical notes.
• Clinical trial design, biomarker discovery, companion diagnostics, dosing, safety, endpoints, or regulatory science.
• Delivering models, patents, software-as-a-medical-device filings, first-author publications, open-source projects, or standards-body contributions.
• Maintaining strong connections with the wider machine learning research community.
• Working effectively across global, matrixed organizations, sites, and therapy areas.
• Using agentic tools to augment rigorous scientific and technical work.
• Assessing emerging AI research and distinguishing meaningful advances from hype.

This is not AI research at arm’s length from its application. You will work alongside scientists, clinicians, statisticians, and technologists on difficult problems where robust technical innovation can support meaningful clinical decisions.

You will join an environment that combines world-class science with cutting-edge technology, encourages collaboration across disciplines, and applies AI where it can make a tangible difference for patients. AstraZeneca’s Enterprise AI messaging emphasizes real-world impact, complex problems, scientific and technological collaboration, and autonomy to innovate within responsible frameworks.

In Oncology, you will contribute in an interdisciplinary setting where AI, novel biomarkers, endpoints, and innovative trial designs can create new possibilities for clinical development.

Bring your expertise. Challenge established approaches. Help shape how AI advances Oncology clinical development.

If you are motivated by technically ambitious AI research and want to see your work applied to some of the most important challenges in Oncology, we would welcome your application.

Join AstraZeneca, where AI meets life-changing impact.
The annual base pay for this position ranges from $124,713.60 - $187,070.40 annually. Our positions offer eligibility for various incentives—an opportunity to receive short-term incentive bonuses, equity-based awards for salaried roles and commissions for sales roles. Benefits offered include qualified retirement programs, paid time off (i.e., vacation, holiday, and leaves), as well as health, dental, and vision coverage in accordance with the terms of the applicable plans.

Date Posted

Closing Date

Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.