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Develop ML models for process optimisation, prediction, and control, including yield, CQAs, aggregation, glycosylation, and impurity profiles.
Apply supervised, unsupervised, and multivariate methods (e.g. neural networks, regression, classification, clustering, PCA/PLS, Bayesian models).
Integrate omics, analytical (LC-MS, spectroscopy), and process data into unified modelling frameworks.
Perform feature engineering informed by bioprocess ...
About the Role
We are seeking a Machine Learning Scientist/Engineer to develop and deploy data-driven models that improve biomanufacturing processes for recombinant proteins, mRNA, cell and gene therapies. The role focuses on applying ML to upstream and downstream process data, analytical datasets, and manufacturing systems to enhance yield, quality, robustness, and process understanding of therapeutics.
Key Responsibilities
Machine learning and data analytics
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