Associate Director - AI Scientist – Computational Radiology

Overview

Associate Director - 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 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 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.

• Support the design and implementation of imaging biomarker strategies for early and late oncology assets, spanning Ph1 to Ph3 clinical studies.
• Lead the design, development, and validation of radiomics, and imaging derived assays, including the creation of robust scoring/quantitation methods.
• 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.
• Work effectively with cross-functional teams to execute defined solutions that drive value to AstraZeneca.
• 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,…