| Location: | London |
|---|---|
| Salary: | £43,981 to £52,586 |
| Hours: | Full Time |
| Contract Type: | Fixed-Term/Contract |
| Placed On: | 3rd November 2025 |
|---|---|
| Closes: | 23rd November 2025 |
| Job Ref: | B04-06755 |
About us
The “Next-Gen Biopharma Manufacturing 5.0” Prosperity Partnership is a 5-year collaborative programme between UCL Biochemical Engineering and AstraZeneca, jointly funded by EPSRC and AstraZeneca. It aims to transform antibody manufacturing using AI, automation, digital twins and advanced analytics to improve production of therapies for cancer, obesity and autoimmune conditions. Delivered through the UCL–AstraZeneca Centre of Excellence, the programme will appoint six postdoctoral researchers to work across UCL and AstraZeneca sites, combining computational and experimental approaches. UCL Biochemical Engineering is a global leader in bioprocess engineering research and education, with a mission to develop innovative biomanufacturing solutions for health and a sustainable bioeconomy. The department combines world-class facilities, strong industrial links, and an interdisciplinary research culture. AstraZeneca is a glob al, science-led biopharmaceutical company with a focus on the discovery, development, and commercialisation of medicines in Oncology, Rare Diseases, and BioPharmaceuticals.
About the role
We are seeking a highly motivated postdoctoral researcher to join this ambitious Prosperity Partnership between UCL and AstraZeneca and to work as part of a cross-disciplinary team across both sites (London and Cambridge). This post is focused on the use of machine learning models of protein interactions to assist the development of therapeutic protein separations, including understanding and addressing host cell protein (HCP) challenges. The successful candidate will explore how machine learning can be used to uncover the pathways by which these HCPs evade separation, and will also work on recommending targeted solutions, such as mobile phase modifiers or small molecule competitors, to enhance separation efficiency. The postholder will lead on advancing model-predictive, high-thro ughput workflows for next-gen purification platforms to accelerate process development, as well as designing and validating predictive modelling tools for purification assessments of next-gen antibody formats using ML and analytics. The role will include leading industrial feasibility studies with AstraZeneca to demonstrate impact. This role is funded for 2 years in the first instance, with potential for extension.
About you
You will hold (or be near completion of) a PhD in a relevant discipline such as biochemical engineering, computational biology, protein chemistry, data science, or related field. You will bring expertise in biological product purification, along with strong data handling and modelling skills. You will have excellent communication skills and the ability to work both independently and collaboratively across teams and institutions. Experience in academic–industrial collaboration would be advantageous. A commitment to UCL’s values and to promoting equality, diversity and inclusion is essential.
What we offer
As well as the exciting opportunities this role presents, we also offer some great benefits, visit https://www.ucl.ac.uk/work-at-ucl/rewards-and-benefits to find out more.
Our commitment to Equality, Diversity and Inclusion
As London’s Global University, we know diversity fosters creativity and innovation, and we want our community to represent the diversity of the world’s talent. We are committed to equality of opportunity, to being fair and inclusive, and to being a place where we all belong. We therefore particularly encourage applications from candidates who are likely to be underrepresented in UCL’s workforce. Our department holds an Athena Swan Gold award in recognition of our commitment and demonstrable impact in advancing gender equality. You can read more about our commitment to Equality, Diversity, and Inclusion here: https://www.ucl.ac.uk/equal ity-diversity-inclusion/
Customer advert reference: B04-06755
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