Director of AI Research, AI for Oncology Clinical Development

This role can be based at AstraZeneca hubs in Barcelona Spain or Cambridge US

Were building a connected end-to-end Enterprise AI engine - uniting data foundations AI technology process reinvention and business-facing AI to accelerate results across the whole value chain. Success depends on being exceptional connectors:youllactivelyleverageexisting capabilities celebrate and promote reuse export breakthrough ideas across geographies and functions and obsess over scaling impact rather than building in isolation. If you thrive in high-collaboration environments where your role is to turn complex cross-functional problems into reusable enterprise-wide capabilities - and where the measure of success is adoption and scale not just innovation - youll have the platform (and sponsorship) to make it real.

About AISI

AI Science & Innovation (AISI) sits at thecentreof AstraZenecas R&D AI transformation. Our remit is to build buy and deliver the AI models and agents that change pipeline outcomes across discovery translational sciencebiomarkersand clinical development.

Drug discovery has benefitted enormously in the current AI era yet comprises only a portion of the journey to bring new treatments to those in need. The final step clinical drug development is oft overlooked despite requiring a significant proportion of time and the AI for Clinical Development team at AstraZeneca were reimagining the process of clinical development. Our vision is to bring safe efficacious treatments to patients in a way that quantifiably improves our chance to do this faster more cost-effectively and with reduced patient burden.

In this role you will be a senior technical and strategic lead to help us leverage the power of AI to the fullest alongside our other computational statistical and machine learning tools. You will work across the enterprise to define and deliver on AstraZenecas most pressing clinical development questions. You will proactively collaborate in cross-functional teams spanning AstraZenecas key Oncology foci of hematology cell therapy antibody-drug conjugates small molecules and biologics. This is an unprecedented high visibility opportunity to invent new ways to leverage data models and learnings across the spectrum of cancer biology and drug modalities and importantly you and the team will apply these new methods to measurably advance the late-stage drug pipeline and our groups ambition.

Responsibilities

• Define and drive the AI strategy and roadmap for Oncology early and late phase clinical development and align AI/ML priorities with clinical and business objectives

• Lead by matrix influence and scientific authority delivery of complex high-stakes AI projects

• Evaluate develop and champion cutting-edge AI methods end-to-end including problem definition data considerations governance algorithm development validation and adoption

• Build cross-functional relationships with clinical development biometrics regulatory and study teams to embed AI strategy and validated solutions into clinical study design execution strategy and decision-making

• Establish and maintain external collaborations with academic institutions technology partners and industry consortia to access novel capabilities and advance the AI roadmap

• Represent AstraZeneca at scientific conferences standards bodies and peer-reviewed venues; contribute first- or last-author publications in leading ML and clinical AI journals

• Establish best practices; help shape and promote team culture

• Mentor and support more junior level scientists within the team

Required qualifications

• PhD in a quantitative discipline such as computer science bioinformatics computational biology mathematics physics biophysics computational neuroscience biostatistics

• 4-8 years work experience outside of PhD with measurable impact (e.g. models delivered patents SaMD filings first-author publications open-source projects standards-body participation)

Technical requirements

• Exceptional software development and coding skills leveraging frontier coding agent frameworks; knowledge of computing hardware a plus

• Deep experience knowledge and understanding of one or more fields of biology

• Deep understanding of machine learning fundamentals with domain expertise in one or more of the following

• Training and tuning foundation models

• Bayesian inference

• Temporal modeling

• Multimodal integration and modeling

• Model calibration and domain adaptation

• Data-centric AI: acquiring creating and curating datasets for model training / post-training / benchmarking / evals

• Model and data evaluations and benchmarking

• Model interpretability

• Model post-training and alignment

Preferred skills

• Deep expertise in cancer biology

• Experience working with biological data such as molecular (e.g. DNA RNA protein) imaging (radiology microscopy) or clinical text (e.g. EHR clinical notes)

• Experience in drug development including but not limited to clinical trial design biomarker discovery companion diagnostics dosing safety endpoints and regulatory

• Experience in a matrixed global organization spanning multiple sites and therapy areas

Soft skills

• Strong proficiency in augmenting but not supplanting daily knowledge work with agentic tools

• Team-oriented mindset

• Ability to proactively and independently deliver high-quality contributions at pace

• Up-to-date with the latest AI research and tools proactively trying out those of interest and ability to discern hype from true added value

• Comfort with ambiguity and a mindset to learn in public prototype early and fail forward

• Excellent written and verbal communication skills
  
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Date Posted

Closing Date

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds with as wide a range of perspectives as possible and harnessing industry-leading skills. We believe that the more inclusive we are the better our work will be. We welcome and consider applications to join our team from all qualified candidates regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment) as well as work authorization and employment eligibility verification requirements.