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Data-Driven Modelling and Optimisation of mRNA Vaccine Manufacture

   Department of Chemical & Biological Engineering

   Applications accepted all year round  Funded PhD Project (UK Students Only)

About the Project

Are you interested in developing platform solutions to overcome pandemics, such as the COVID-19 pandemic, and other diseases? More specifically, are you interested in developing digital tools for driving the development and operation of RNA vaccine & therapeutics production processes for enabling rapid, high volume, low-cost and high-quality vaccine and therapeutics production against a wide range of diseases?

If yes, we invite applications for a 3.5 year funded PhD studentship to work under the supervision of Dr Solomon Brown at the University of Sheffield. We are working on an impactful, fast-paced and exciting project aiming to innovate RNA production processes for therapy and pandemic preparedness.

The RNA vaccine platform technology has been successfully used to develop COVID-19 vaccines at record speeds. Although this first iteration of RNA vaccines was clinically successful, there is still substantial room for improving the production processes to increase production rates and volumes, and to reduce costs, whilst maintaining consistently high product quality. The demand for RNA production capacity is projected to increase given the success and platform nature of this technology. Besides COVID-19 vaccines, the mRNA platform technology is in prime position to promote rapid development and mass-production of mRNA vaccines against seasonal influenza with much shorter timelines, Rabies, Zika, Human Papilloma Virus, Hepatitis C, Malaria, HIV, immune disorders, cancer as well as against currently unknown, future viral targets. There is substantial room to develop computational models, digitise and automate the RNA platform technology for speeding up product-process development, enhancing production rates and production volumes, reducing costs and assuring high product quality. 

The aim of this studentship is to develop and optimise the data-driven modelling approaches using Machine Learning techniques to enable the monitoring of difficult to measure critical quality attributes (CQAs) to enable the real-time control of the unit-operations and systems involved in the manufacture. During the project, you will gain experience in developing and applying Machine Learning techniques to bioprocessing, process analysis and mRNA manufacture. You will also learn to integrate the developed bioprocess models into the Quality by Digital Design framework.

You will be part of a team of process developers, process modellers, analytical experts and data scientists, all working together to innovate RNA vaccine and therapeutics production processes.

Please see this link for information on how to apply: Please include the name of your proposed supervisor and the title of the PhD project within your application.

A first class or upper second class honours degree in engineering, computer science or related mathematical discipline, or a merit or distinction in a suitable MSc. Experience working in numerical modelling and an interest in biopharmaceutical manufacture is desirable. If English is not your first language then you must have an International English Language Testing System (IELTS) average of 6.5 or above with at least 6.0 in each component, or equivalent. Please see this link for further information:

The start date is as soon as possible, the latest start date is in October 2022.

For more information contact: .

Funding Notes

The 3.5 year fully funded studentship is available to UK students. The funding includes:
● Research Council Stipend (Estimated £16,000 Per Year)
● Tuition Fees at the UK Fee Rate (£4,567 Per Year)
● Research Support and Training Grant (RTSG)

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