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Data-Analytics/Visualisation Platform for mRNA Manufacturing


   Department of Chemical & Biological Engineering

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  Dr Peyman Moghadam, Dr Zoltán Kis  Applications accepted all year round  Funded PhD Project (UK Students Only)

About the Project

Are you interested in applying your data science expertise in Industry 4.0 vaccine manufacturing? As part of a Wellcome LEAP project, we have an exciting opportunity for someone with a passion for the application of data science and machine learning in digital manufacturing. This project aims to digitise and automate the RNA production process for therapy and pandemic preparedness.

We invite applications for a 3.5 year funded PhD studentship to work under the supervision of Dr Peyman Z. Moghadam at the University of Sheffield. We are working on an impactful, fast-paced and exciting project aiming to innovate RNA production processes.

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 digital tools for analysing and visualising big data from the RNA platform production technology, to allow better and more user-friendly process monitoring, understanding and operation.

In this PhD project, we will create a bespoke data analytics platform that is capable of analysing and plotting historic and real-time process data, similar to a data historian. This platform will have the ability to create a multitude of data visualizations. The visualizations will be displayed on an enterprise quality dashboard allowing for users to customize what key performance indicators are displayed and where these are displayed. The dashboard will allow the user to apply and execute various analytical techniques including statistical methods, dimensionality reduction, and noise reduction in the data. By combining the dashboard with IoT for condition and process monitoring, machine learning algorithms can be added to the platform to make use of cutting-edge industry 4.0 techniques such as predictive quality control. Lastly this platform will be used for capturing and creating insights from data created by digital twins and other data driven models.

The ideal candidate will have or expect to achieve a first-class honours degree or equivalent in computer/data science and/or any other engineering discipline. Experience in programming e.g. in Python and Java is desirable. This is a multidisciplinary project and the successful candidate will benefit from working collaboratively with other data analysts/scientists and process modellers, all working together to innovate RNA vaccine and therapeutics production processes. 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: https://www.sheffield.ac.uk/postgraduate/phd/apply/english-language.

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.

Applicants should have a first class or upper second-class honours degree in computer science, data science, (bio)chemical engineering or a related discipline, or a merit or distinction in a suitable MSc. Experience working in on a coding/project, in manufacturing digitisation or data science is desirable. All applicants should have a strong interest in data science, data visualisation, programming and mRNA vaccine and therapeutic manufacture. 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: https://www.sheffield.ac.uk/postgraduate/phd/apply/english-language.

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

For more information email Dr Peyman Z. Moghadam at


Funding Notes

The fully funded studentship is available to UK students.

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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