Associate Principal Scientist, AI and Computational Tools, Oncology R&D (1-year FTC) in Cambridge

Associate PrincipalScientist,AI and Computational Tools,Oncology R&D

Contract: 1-year fixed-term contract

Location:Cambridge, UK .

Introduction to the Role:

At AstraZeneca, we turn ideas into life changing medicines. Working here means being entrepreneurial, thinking big and working together to make the impossible a reality.We’repassionate about the potential of science to address the unmet needs of patients around the world. We commit to those areas where we believe we can really change the course of medicine and bring bignew ideasto life.

About the Role:

We areseekinga highly motivated,independentand collaborative Associate Principal Scientist to join our Immune Cell Engagers Discovery group in Cambridge, UK, on a 1-year fixed-term contract.This role sits at the intersection of immuno-oncology biology, computational datascienceand applied AI, and is central to how we build and embed AI-first workflows across our discoverygroup.

You will combine scientific domainexpertisewith strong software and data-engineering skills to lead the design and deployment of AI-powered tools, shape robust data-infrastructurestrategiesand serve as arecognisedAI Architect for the group. You will provide technical leadership across multiple initiatives,identifyopportunities, proposesolutionsand build capabilities that can be adoptedmore widely across Oncology R&D.

Working closely with wet-lab scientists, data scienceteamsand R&D IT, you will translate experimental data into scalable,reproducibleand insight-generating systems, while supportingcolleagues toadoptAI-enabled approachesand strong data practices.

Main Duties and Responsibilities

• Lead the design, development, deployment and lifecycle management of AI-powered tools and workflows, including data-wrangling pipelines,visualisationapplications, agentic AIsolutionsand LLM-integrated tools.Ensuresolutions are maintainable, adopted byusersand deliver measurable scientific value.

• Lead the development and evolution of data infrastructure and data standards for the discovery group, with the intended outcome of structured, quality-controlledand reproducible data that are ready for analysis and AI applications.

• Act as an AI Architect and technical subject matter expert for the department, defining best practices, guiding technology choices, influencing AIstrategyand driving adoption of reusable code,packagesand tools across teams.

• Identify,prioritiseand lead delivery of AI and computational capability projects that address strategic scientific challenges, balancing innovation, technical feasibility, governance,sustainabilityand user adoption.

• Mentor and support colleagues in adopting AI-enabled approaches,reproducible dataworkflowsand practical coding practices.

• Lead cross-functional collaborations with Data Science, R&D IT and platform teams to deliver scalable solutions, align technical and scientific standards, and influence broader computational capabilities across Oncology R&D.

• Develop and applyagentic workflowsto extract biological insight from high-dimensional datasets, including single-cell and spatial transcriptomics, functional screeningdataandmultiomicintegration.

• Stay current with advances in computational biology and AI methods,toolsand best practices. Proactively evaluate and adopt fit-for-purpose approaches that strengthen discovery workflows.

• Prepare and deliver clear scientific and technical presentations within the Immune Cell Engagers Discovery group, across Oncology R&Dand torelevant leadership audiences.

• Ensure compliance with internal standards and externalregulations, andmaintainaccurateandtimelyrecords in the electronic laboratory notebook.

EssentialRequirements

• Demonstrated experience leading complex computational or AI initiatives from concept through implementation,deploymentand adoption within a scientific environment.

• Demonstrable experience usingagentic AI frameworks, LLM integration or AI-assisted coding toolssuch asGitHub Copilot, Claude Code or similar in a research or production context.

• Demonstrableexperience developing and deploying tools for use by others, such as Shiny applications, automated reportingsystemsor shared analysis packages, with confidence in version control and collaborative software-development practices.

• Demonstrableexperience buildingresearchdata infrastructurethat enables structured, quality-controlledand reproducible data, for examplethroughLIMS schemas,electronic laboratory notebook workflows, structured databasesorreproducible data pipelines with automated validation and quality control.

• Strongproficiencyin Python and/or R, and experience of large-scale data management.

• Demonstrated ability tosupportadoption of new computational capabilities across research teams, including user engagement, documentation,trainingand communication with scientific leadership.

• Evidence of influencing scientific or technical direction beyond an immediate project team through technical leadership, best-practice development,mentoringor capability building.

• Strong interpersonal and collaboration skills, witha track recordof working effectively across wet-lab and dry-lab teams in a matrixed environment.

• Experience preparing written scientific reports and delivering oral presentations.

Desirable Skills

• PhD in relevant disciplines or equivalent experience (e.Software Engineering,Computational Biology,Machine Learning, Data Science, or related fields).

• Experience with advanced deep learning model families (graph neural networks, transformers, probabilistic models) applied to biological data.

• Experience with datascienceplatforms such as DominoorQuartzBio.

• Experience working withbiological datasets in immunology,oncologyor related therapeutic areas, with the ability to rapidly gain domain knowledge as needed.

• Experience in an industry drug discovery setting, with knowledge of discovery-stage decision-making.

What You Will Gain

You willoperateat thecutting edgeof oncology discovery, combining AI and data engineering with deep immunology to accelerate target discovery, mechanism-of-actionstudiesand candidate selection.The roleprovidesan opportunity to applycutting-edgeAI approaches to large-scale biological and translational datasets, working directly with scientists generating novel experimental data.You will help shapehow the Immune Cell Engagers Discovery group integrates AI into its daily workflows,building tools that colleagues rely on andstrengthening practical, reproducible approaches toAI-enableddiscoveryscience.

Where can I find out more?

Our Social Media,

• Follow AstraZeneca on LinkedIn :

• Follow AstraZeneca on Facebook :

• Follow AstraZeneca on Instagram :

Date Posted

25-Aug-2026

Closing Date

10-Sep-2026Our mission is to build an inclusive and equitable environment. We want people to feel they belong at AstraZeneca and Alexion, starting with our recruitment process. We welcome and consider applications from all qualified candidates, regardless of characteristics. We offer reasonable adjustments/accommodations to help all candidates to perform at their best. If you have a need for any adjustments/accommodations, please complete the section in the application form.

#J-18808-Ljbffr