About the Project
Biopharmaceuticals have recently proved as highly successful clinical drugs, therefore driving industrial biotechnology towards their large-scale production. However, widely-used cell lines are very inefficient at producing desired compounds. In this regard, modelling and culture bioengineering have shown promising results in identifying the optimal interventions for optimising the biological processes of biopharmaceutical production.
The aim of this project is to combine machine learning techniques with fundamental rheological and colloidal modelling to characterise and optimise culture conditions. We will therefore investigate if, compared to conventional optimisation techniques, combining deterministic modelling with data-driven machine learning methods can lead to superior bio-process design and development (“quality-based design”). The ultimate objective of the project is to propose optimal growth conditions for maximising production of target therapeutic compounds.
North East England’s universities are joining forces under a £3.9m scheme, funded by the European Regional Development Fund, to connect the region’s businesses with research to encourage growth & job creation. Teesside University is delighted to be able to offer a number of part funded industrial PhDs to eligible SMEs in the north east. This project is funded by the University & European Regional Development Funding & looks to support local firms with their research & development needs, developing new products & services in key sectors & creating high quality jobs in the local economy.
Entry Requirements
Applicants should hold or expect to obtain a relevant degree at 2.1 minimum, or an equivalent overseas degree in engineering, mathematical modelling, computer science, computational biology, physics, or related subjects. Candidates with expertise in modelling and machine/deep learning are particularly welcome to apply.
International students would be subject to the standard entry criteria including English language, ATAS clearance & Tier 4 procedures. Please contact the [Email Address Removed] for further information.
About Teesside University
The School of Computing, Media and the Arts at Teesside University conducts research on a wide range of topic areas including Computer Science, Artificial Intelligence, Software Engineering, Cyber-Physical Systems, Computer Games, Animation, Media and Fine Art. In REF 2014, 69.8% of our research outputs in Computer Science and Informatics was recognised as world-leading or internationally excellent. For more information: http://www.tees.ac.uk/sections/research/computing/about.cfm
About Procellia
Procellia, a NETPark-based company, is developing a predictive optimisation system for industrial biological processes including fermentation and cell culture. It is based on cell modelling and therefore a fundamental part of this optimisation platform comprises the development of predictive algorithms for generating optimal control solutions.
How to Apply
Please apply online for this opportunity; using the PhD full time application form & ref: IIIP0004
Funding Notes
Applications are welcome from strong UK, EU & International students. The studentship covers tuition fees at the Home/EU rate for three years & provides an annual tax-free stipend of £15,000 p.a. for three years, subject to satisfactory progress. Non-EU International students will be required to pay the difference between the Home/EU & International fee rate (approx. £7,350 per year).
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