Loughborough University is a top-ten rated university in England for research intensity (REF2014). In choosing Loughborough for your research, you’ll work alongside academics who are leaders in their field. You will benefit from comprehensive support and guidance from our Doctoral College, including tailored careers advice, to help you succeed in your research and future career.
Project overview:
This PhD project will be part of a multi-institutional EPSRC programme; Made Smarter Innovation – Digital Medicines Manufacturing Research Centre which involves 3 universities (Strathclyde, Loughborough, and Cambridge) and key industrial players from the pharmaceutical and digital technology sectors. The overall objective of the research centre is to (i) accelerate the adoption of industrial digital technologies in the pharmaceutical sector, (ii) transform medicines development, manufacturing, quality control and supply chain (iii) reduce costs, lead time and wastes, (iv) enhance flexibility and resilience, and (v) address the digital skills gap and provide the pharmaceutical industry with the next generation digital leaders. This project will be based in the Department of Chemical Engineering. Following a recent £25 million refurbishment, the department houses a range of state-of-the-art laboratory facilities and a modern office environment. The PhD student will join a dynamic and vibrant research team and will benefit from the support of several postdoctoral research associates and PhD students.
Project Details:
This PhD Project will build and help deploy new industrial digital technologies for downstream pharmaceutical processing dedicated to the formulation of solid dosage forms. The project will firstly develop and validate novel strategies for smart and optimal design of experiments to build reliable and predictable mathematical models, digital twins, and soft sensors. The project will also develop strategies for digital quality control by real-time optimisation and control which may require a combination of data-driven and model-based approaches to identify and optimise the design spaces, where the critical quality attributes of the pharmaceutical products can be guaranteed. The impact of uncertainties will be captured by a robust design space and integrated to a hierarchical optimisation and control platform. The project will also develop robust real-time optimisation and Artificial Intelligence strategies to help identify robust operating ranges and optimal operating trajectories. The PhD student will codevelop some of these digital technologies and methodologies with our research team in close collaborate with our research and industrial partners, particularly the research team leading the deployment of the autonomous pharmaceutical plant at Strathclyde University.
Entry requirements:
Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) and a relevant Master’s degree in Chemical Engineering or related subject.
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