Senior AI Scientist – Computational Radiology Full-time NEW

Senior AI Scientist – Computational Radiology

Location: Boston, MA

At AstraZeneca, we put patients first and strive to meet their unmet needs worldwide. Working here means being entrepreneurial, thinking big and working together to make the impossible a reality. If you are swift to action, confident to lead, willing to collaborate, and curious about what science can do, then you're our kind of person.

We are seeking a medical computer vision and AI expert to lead the development of radiology imaging derived biomarkers for our Radiology & Theranostics (R&T) team within the Cancer Biomarker Development (CBD) group. Our R&T team plays a crucial role in supporting AstraZeneca's early oncology and late development strategy for an innovative pipeline that includes Antibody-Drug Conjugates (ADCs), Radio-conjugates, T-cell engagers, CAR-T therapies, bispecific antibodies, and small molecules.

In this role, based in Boston, MA, you will collaborate with a diverse team of radiologists, imaging scientists, radiation physicists, translational scientists, biologists, and oncologists. This unique opportunity allows you to contribute to the development of new biomarkers, enabling indication selection, early assessment of biological activity, and optimal patient stratification. Your efforts will significantly enhance the probability of success for AstraZeneca's oncology pipeline.

The “AI Scientist – Computational Radiology” will work to leverage foundational and cutting-edge techniques to manipulate and process medical image data, in combination with business domain knowledge, to develop and apply advanced modelling and simulation algorithms (e.g. deep learning, foundational models, traditional Machine learning including classification, regression, clustering, graph theory, Monte-Carlo sampling, and more) to generate business and scientific insights. The role will work within defined project scope and solutions aligned to established governance frameworks and policies.

Responsibilities:

• Lead the design, development, and validation of radiomics, and imaging derived computational pipelines, including the creation of robust image enhancement, reconstruction, and quality scoring/quantitation methods.
• Deliver image analytics data to inform indication selection and identify optimal patient populations.
• Develop, implement, and support modeling solutions that interrogate complex, multimodal datasets to generate scientific and business insights, applying appropriate techniques across image analysis and machine learning, including classification, regression, clustering, graph‑based, and related approaches.
• 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.

Qualifications:

• PhD in Bio-Medical/Electrical Engineering/Nuclear Medicine, or relevant discipline with 0-1 years of experience in the industry working with a strong understanding of medical imaging physics, medical image analysis, and state of the art computer-vision methods.
• Demonstrated experience in building Computer Vision, AI models, with a sound understanding of GPU optimized computational pipelines, relevant statistical and machine learning methods and standard Machine Learning practices, and a desire to continue to learn and develop these skills.
• 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.

Desirable for the role:

• Experience with different medical imaging modalities – Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), etc.
• Experience with, and understanding of sophisticated medical image reconstruction methods, especially PET and SPECT, including Monte-Carlo approaches.
• Experience developing and applying machine learning approaches in multimodal analytical settings, integrating medical imaging with clinical, molecular, or other biomedical data sources.