Senior Multimodal AI Scientist – Computational Radiology

AstraZeneca • Cambridge, MA

1d • $124,714 - $187,070 • Onsite

About The Position

AstraZeneca is seeking an AI and machine learning scientist to develop computational biomarkers and predictive models from multimodal biomedical data, including radiology imaging, clinical, molecular, and other patient-level data, for their Computational Radiology team within the Biomarker Sciences & Technologies (BST) group. This team supports AstraZeneca’s early oncology and late development strategy for an innovative pipeline. The role is based in Boston, MA, and involves collaboration with a diverse team of specialists to contribute to the development of new biomarkers for indication selection, early assessment of biological activity, and optimal patient stratification, thereby enhancing the probability of success for AstraZeneca's oncology pipeline. The scientist will leverage foundational and cutting-edge techniques to drive the development of computational biomarkers and advanced predictive models by integrating radiology imaging with clinical, molecular, pathology, and other biomedical data sources. This involves applying advanced modeling and simulation algorithms, such as deep learning, foundational models, and traditional machine learning techniques, to generate business and scientific insights within defined project scopes and aligned to established governance frameworks.

Requirements

• Bachelors Degree in Computer Science, Statistics, Biostatistics, Machine Learning, Biomedical Engineering, Computational Biology, Bioinformatics, Applied Mathematics, Physics, or related quantitative discipline with 0-1 years of experience in the industry with a strong foundation in machine learning, statistical modeling, applied mathematics, computer vision, computational biology, bioinformatics, biomedical engineering, or related quantitative disciplines.
• Demonstrated experience building end-to-end ML pipelines including data preprocessing, model development, validation and performance assessment.
• Practical software development skills in standard data science tools: Python, R with demonstrable knowledge of good coding practices.
• Strong track record of publications in quality conferences and journals.
• Strong communication skills: ability to present compelling cases to collaborators and operate dynamically to identify solutions.
• Ability to work effectively within a team.

Nice To Haves

• Prior experience in medical imaging, computational pathology, genomics, clinical data science, or other biomedical data domains is valued.
• Experience developing and applying machine learning approaches in multimodal analytical settings, integrating medical imaging with clinical, molecular, or other biomedical data sources.
• Expertise in statistical learning methods for high-dimensional data, including multiple testing correction and feature selection.

Responsibilities

• Lead the design, development, and validation of computational pipelines that generate robust biomarkers and predictive models from multimodal biomedical data, including imaging, clinical, molecular, and real-world datasets.
• Develop machine learning and statistical modeling approaches that identify patient subgroups, predict outcomes, and generate clinically actionable insights from high-dimensional multimodal datasets.
• Develop, implement, and support modeling solutions that interrogate complex, multimodal datasets to generate scientific and business insights, applying modern machine learning, statistical learning, representation learning, foundation models, causal inference, and related computational approaches where appropriate.
• Design and implement multimodal analytical frameworks that integrate imaging data with clinical, molecular, and other non‑imaging data sources to support patient stratification and endpoint prediction.
• Researching and developing predictive and explainable computational methods to guide decision-making within project parameters and established approaches.
• Present or publish findings for conferences and in peer reviewed journals.
• Builds effective relationships with established range of stakeholders to ensure utilization and value of information resources and services.
• Clearly and objectively communicate results, as well as their associated model assumptions, uncertainties and limitations within agreed frameworks.
• Develop, maintain, and apply ongoing knowledge and awareness in trends, standard methodology and new developments in analytics and data science.
• Implement good working practices to ensure that computational radiology work is delivered to robust quality standards and aligned to defined governance frameworks and policies.
• Collaborates in a multidisciplinary environment with world leading clinicians, data scientists and statisticians, biological experts, clinical trial delivery teams, and IT professionals.

Benefits

• qualified retirement program [401(k) plan]
• paid vacation and holidays
• paid leaves
• health benefits including medical, prescription drug, dental, and vision coverage

What This Job Offers

• Job Type: Full-time
• Career Level: Senior