Postdoctoral Research Assistant – Managing Chemical Uncertainty

Postdoctoral Research Assistant–Managing Chemical Uncertainty

Cambridge,UKorMacclesfield, UK 

Competitive salary and benefits 

Are you passionate about applying AI and cheminformatics to solvereal analyticalchemistry challenges? Do you thrive working at the interface between disciplines, turning complex problems into practical solutions? This role offers the opportunity to develop innovative tools that will change how AstraZeneca handles impurity tracking and analytical data interpretation across the drug development pipeline.

What we do

AstraZeneca’s Pharmaceutical Sciences function delivers the therapies of the future, accelerating molecules from idea to clinical reality through pioneering science, technological innovation, and digital transformation. The Digitisation team partners closely with scientists, engineers, and IT to create and embed robust, user-centric informatics and automation solutions across the CMC spectrum—driving seamless data capture, integration, and scientific insight.

The role

As a Postdoctoral Research Assistant, you will lead the development of an innovative system for managing chemical uncertainty in analytical experiments. Working at the intersection of cheminformatics, AI, machine learning, and analytical sciences,you'lltackle two key challenges:representingchemical uncertainty in a computationally tractableway andcreating the tools and data standards that enable scientists to make faster, more informed decisions.

This is atwo-yearfixed-term position, offering the chance to work on a high-impact project that addresses critical gaps in current analytical workflows and regulatory compliance.

Your responsibilities will include:

• Develop novel approaches forrepresentingchemical uncertainty:In collaborationwith leading academics (including Professor Jonathan Goodman at University of Cambridge) you will create computational methods and data standards that enable robust handling of incompletely characterised molecules in analytical workflows.

• Build AI-driven systems for impurity tracking: Design and implement machine learning solutions that can track and link chemical observations across experiments as understanding evolves.

• Create tools that transform how analytical data is interpreted: Develop platforms that enable continuous learning, intelligent querying, and automated insights to accelerate decision-making in drug development.

• Bridge computational prediction and experimental reality: Integrate predictive models with analytical data to refine understanding andvalidateapproaches against real-world pharmaceutical challenges.

• Collaborate across disciplines: Work with analytical chemists, data scientists, and pharmaceutical development teams to ensure your solutions address genuine scientific needs and integrate effectively.

• Drive adoption and share knowledge: Present your work to stakeholders, contribute to publications, and support scientists inleveragingnew capabilities within their research.

• Contribute to the broader scientific community: Engage with academic collaborators and help advance how the field handles chemical uncertainty and analytical data.

Expected background for the role

• PhD in Cheminformatics, Computational Chemistry, Computer Science, Data Science, Machine Learning, Analytical Chemistry, or a related discipline, with a strong publication record and proven experience in at least one of: AI/machine learning development, cheminformatics, computational chemistry, or analytical data analysis

• Hands-on coding ability in Python (or similar languages), with experience applying computational methods to chemical or analytical problems.

• Understanding of either cheminformatics concepts and molecular representations, or analytical chemistry workflows and data interpretation (depth in one area is valued over breadth across all).

• Experience working with complex, real-world datasets and an appreciation for handling uncertainty and incomplete information.

• Strong problem-solving, teamwork, and communication skills, with the ability to bridge computational and experimental science.

Why AstraZeneca

Join us andyou’lldirectly power new levels of scientific discovery and delivery, collaborating with an inclusive team at the forefront of digital transformation in pharmaceutical R&D.You’llhave opportunities for continuous learning, career growth, and lasting impact on global patient outcomes.

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