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Physics-Informed Artificial Intelligence Approach for Drug Manufacturing

   Department of Chemical & Biological Engineering

   Friday, September 30, 2022  Funded PhD Project (European/UK Students Only)

About the Project

Fully Funded PhD Studentship for UK students. Pharmaceutical industry is transitioning from traditional batch operations to continuous processing and predictive models will greatly facilitate this transition. As sensors and monitoring equipment are increasingly employed, valuable data on the critical material attributes, process parameters and quality attributes are now possible to be acquired in real-time through process analytical technology. It is expected that the next decade will see step changes in data-driven technology, impacting all aspects of the process industries. While the state-of-art machine learning models have great potential for process control and operations, machine learning alone ignores the fundamental laws of physics and makes predictions with little or no interpretability. Multiscale modelling can act as a complement to define the physical constraints of the design space, generate numerical data to enrich the data volume and elucidate mechanisms that explain the emergence of functions.

Therefore, this PhD project is focused on developing and implementing a Physics-Informed Artificial Intelligence approach for modelling industrial drug manufacturing processes and the use of Augmented Reality for process design. The candidate will be trained with the state-of-the-art deep learning model developments and gain experience in its application in real industrial problems. The candidate will be provided with the opportunity to join a collaborative project working with leading companies including IBM, Siemens, Pfizer, AstraZeneca and GSK.

Please see this link for information on how to apply: https://www.sheffield.ac.uk/cbe/postgraduate/phd/how-apply. Please include the name of your proposed supervisor and the title of the PhD project within your application.

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