AI Research Lead, Mechanistic and Machine Learning Models

AI Research Lead, Mechanistic and Machine Learning Models

Introduction to role

In 2025 within just the United States, over 2 million people are projected to be diagnosed with cancer. Along with heart disease, cancer is the leading cause of death across all ages. Cancer patients’ remaining lives are often measured in months, not years. How can we extend the recent advances in ML and AI to tackle cancer? How do we determine which patients should receive which drugs, especially if the drugs are still being developed? Will the drugs be safe? How much or how often should a drug be taken? What combination of drugs should be used?

The AI Research team in Oncology reports directly to the Chief Data Scientist, with a broad remit to develop and deliver new algorithms, models, and research that can propel the next generation of Oncology drug discovery and clinical development. Join us to build the future of AI in biology and to solve cancer!

Accountabilities

You will help build next-generation AI models to power AstraZeneca’s bold ambition to launch 20 new medicines by 2030. You will bring your deep knowledge of applied mathematics, statistics, and machine learning to accelerate delivery of mechanistic and foundation models. You will use data from real patients tested with real drugs to model and understand treatment outcomes. You will devise creative solutions to scale up and model multimodal datasets (e.g., DNA, RNA, protein, tumor imaging, tissue imaging, spatial ‘omics). You will work collaboratively in a close-knit team, bringing your unique skillset, and with a sense of urgency to do what it takes for the team to win.

Essential Skills/Experience

• PhD in applied mathematics or similar computational discipline (e.g., bioinformatics, computer science, computational biology, computational neuroscience, physics, mathematics) and 5+ years’ experience in a machine learning & AI research & development setting (or postdoctoral experience plus 2+ years’ experience).

• Deep understanding of agent-based simulations, mathematical models, continuum models, and/or machine learning fundamentals, plus technical domain expertise in one or more of the following areas:

  • modeling of disease progression and response to treatment,

  • multimodal modeling (e.g., vision-language models, multi-task models, multi-omic models),

  • high-throughput simulations and reduced-order analytical models,

  • LLMs and transformer models (algorithms, training, fine-tuning), datasets and benchmarks

• First author publications in high-profile journals such as Nature, Nature Physics, Nature Communications, or leading machine learning conferences such as NeurIPS, ICML, and ICLR.

• At least 2 years experience in biotech or big pharma leading research program related to clinical data, preferably in oncology.

• Demonstrated capability to plan and develop AI strategy and manage multiple stakeholders.

Desirable Skills/Experience

• Excellent written and verbal communication skills

• A problem-solving approach

• Integrity, responsibility, humility, and open-mindedness

• Initiative, proactivity, practicality, independence, and ownership

• Team-oriented mindset

• Experience mentoring junior scientists

• Ability to execute and iterate at pace

Benefits: hybrid work with 3 days in-office per week  

When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

AstraZeneca offers an inspiring learning environment where every setback is seen as a chance to improve. Our supportive yet challenging approach pushes us towards groundbreaking solutions. We are dedicated experts who combine specialist knowledge with curiosity, always searching for better ways of doing things. Working here means contributing to something that truly matters—using our skillset to make an important difference to society and patients across the globe.

AstraZeneca is where science meets data to develop bold solutions. We seek the best solutions using data to positively impact science. We don't accept the status quo; we dig deep to see what the data is telling us and use cutting-edge methodologies and models to drive scientific breakthroughs. Our supportive yet challenging approach creates an inspiring learning environment where every setback is seen as a chance to improve.

Ready to make a difference. Apply now!

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.