PhD Vacancy: Plant-wide dynamic mathematical modelling and optimisation of integrated continuous pharmaceutical manufacturing processes

Computational tools and model-based optimisation, control and more broadly decision-making methods and applications have grown dramatically over the last decade and opened opportunities for a new generation of digital representation and simulation tools referred to as Digital Twins. A Digital Twin provides a virtual and yet a living and interactive replica of a physical system, process or product. It offers an augmented simulation and visualisation platform and expected to become a standard capability in all industries in near future. The pharmaceutical and biopharmaceutical industries are undergoing a paradigm shift with the development and adoption of more flexible regulatory tools, agile lean and cost-effective continuous manufacturing technologies as well as robust decision-making systems. There are urgent and unprecedent needs for more reliable and predictable simulation tools for model-based design, optimisation and control which came with a real transformation of the pharmaceutical job market.
This PhD project will look at the development and validation of new strategies to build high fidelity dynamic models and integrated digital twins of a continuous pharmaceutical processes with self-optimising capabilities. The focus of the project will be mainly modelling and simulation but also potentially experimental validation that can be conducted by the PhD student or research collaborators. This PhD Project will benefit from our strong and well-established expertise in mathematical modelling, simulation and process control. It will also be conducted as part of the Future Continuous Manufacturing and Advanced Crystallisation Research Hub (CMAC HUB), a world-class consortium involving more than 30 industrial and academic partners, including 8 Big Pharma companies (e.g. GSK, Novartis, Astra Zeneca, Roche, Pfizer). Initial studies would focus on a continuous crystallisation stage, but then the methodology would be extended to include downstream isolation steps, leading to a seamless fusion of physical and data-driven model implementations.

Primary supervisor: Dr Brahim Benyahia  (Department of Chemical Engineering)
Second supervisor: Prof Chris Rielly  (Department of Chemical Engineering)

Funding: 3 year studentship starting October 2020
  • UK/EU students: UK/EU tuition fees and the National Minimum Doctoral Stipend (£15,009 for 2020/21)
  • International students: fees only and stipend needs to be covered by a different source

How to Apply
: Applicants should send a CV, contact details of 2 references and a covering letter to Dr Brahim Benyahia,

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