AI Research Scientist

AstraZeneca•Cambridge, MA

2d•$124,714 - $187,070•Hybrid

About The Position

AstraZeneca is seeking a Senior Scientist to apply artificial intelligence, machine learning, statistics, and computational science to oncology clinical development. The role is a technical contributor in cross-functional, matrixed teams, developing and applying robust AI approaches to clinical study design, execution, strategy, and decision-making. The work may span cancer biology and multiple drug modalities, including hematology, cell therapy, antibody-drug conjugates, small molecules, and biologics. The position offers the opportunity to contribute to real clinical-development challenges and AstraZeneca’s late-stage Oncology pipeline. The scientist will lead technical delivery of complex AI initiatives; evaluate and develop methods across problem definition, data strategy, governance, algorithm development, validation, and adoption; and develop novel AI solutions. The role also includes building external collaborations, representing AstraZeneca in scientific forums, publishing research, and sharing technical knowledge and standards across the team. The position is based in Cambridge, USA, with three days in the office and two days remote.

Requirements

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.
Deep understanding of machine learning fundamentals.
Strong expertise in one or more of the following: 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; or multi-agent systems and agent harnesses.

Nice To Haves

Experience in biology or biomedical research.
Experience applying machine learning to molecular data, including DNA, RNA, or proteins.
Experience working with imaging data such as radiology or microscopy.
Experience working with clinical text, electronic health records, or clinical notes.
Experience with clinical trial design, biomarker discovery, companion diagnostics, dosing, safety, endpoints, or regulatory science.
Experience delivering models, patents, software-as-a-medical-device filings, first-author publications, open-source projects, or standards-body contributions.
Strong connections with the wider machine learning research community.
Ability to work effectively across global, matrixed organizations, sites, and therapy areas.
Experience using agentic tools to augment rigorous scientific and technical work.
Ability to assess emerging AI research and distinguish meaningful advances from hype.

Responsibilities

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 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.