Associate Director – AI Scientist – Computational Radiology Full-time

Associate Director – AI Scientist – Computational Radiology

Location: Boston, MA

Hybrid: 3 days in office

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 scientific and organizational leader in computational radiology and multimodal biomarker development who will drive strategy, scientific vision, and cross-functional influence across oncology programs 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:

• Support the design and implementation of imaging biomarker strategies for early and late oncology assets, spanning Ph1 to Ph3 clinical studies.
• Provide scientific leadership for multimodal biomarker development, including radiomics, deep learning biomarkers, functional imaging readouts, and imaging–molecular fusion approaches, including the creation of robust scoring/quantitation methods.
• Drive cross-functional influence by shaping biomarker strategy, navigating complex matrixed environments, and influencing stakeholders without formal authority.
• Deliver image analytics data to inform indication selection and identify optimal patient populations.
• Facilitate informed biomarker selection by applying knowledge of the mechanisms of action, pharmacodynamics, and pharmacokinetics of the therapeutic agents.
• Assist in the development, and evaluation of Clinical Trial Prototype imaging assays and Companion Diagnostics (CDxs) in collaboration with diagnostic companies and CROs
• Develop, implement, and support modelling solutions designed to drive the interrogation of datasets for insights in scientific and business application areas within defined project scope. This includes integrating data from multiple different sources and modalities and includes the application of specialized approaches in image analysis, classification, regression, clustering, graph theory and/or other techniques.
• Researching and developing predictive models and 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 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 with 2 years of experience or Masters with over 5 years of experience in the industry working with a strong understanding of medical image analysis.
• Demonstrated leadership experience influencing scientific and strategic decisions without authority, driving multidisciplinary alignment, and communicating complex concepts to senior stakeholders.
• Demonstrated experience with a sound understanding of a variety of statistical and machine learning methods and standard development 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.

Desirable for the role:

• Experience with different medical imaging modalities – Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), etc.
• Experience working with MONAI tooling.
• Experience within the life sciences industry.
• Multi-GPU optimization of 3D computer vision architectures
• Sophisticated statistical and machine learning models such as hierarchical mixed Bayesian models, vision transformers, longitudinal data analysis.