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continuous operations at lab scale. In Situ Product Recovery (ISPR) evaluation: Test ISPR methods to boost productivity and energy efficiency. Bioprocess modelling: Employ simulation, techno-economic analysis
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tissue, radiologists insert a localisation device (RFID, magnetic seed) into the tumour pre-operatively. Wireless methods hold promise however, due to the scale of current RFID tags, delivery is
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on empirical optimisation, leading to inefficiencies in energy use and impurity removal. This PhD project proposes to develop a Coupled Computational Fluid Dynamics-Discrete Element Method (CFD-DEM) model
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/C6 sugar utilisation and tolerance. Fermentation trials: Optimise batch, fed batch, and continuous operations at lab scale. In Situ Product Recovery (ISPR) evaluation: Test ISPR methods to boost
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) into the tumour pre-operatively. Wireless methods hold promise however, due to the scale of current RFID tags, delivery is problematic for both clinicians and patients. The PhD provides an opportunity to develop
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. Link to the event can be found here: https://events.teams.microsoft.com/event/376b2195-d8da-47c0-86e2-b18813ec19e3@4a5378f9-29f4-4d3e-be89-669d03ada9d8 . Number Of Awards 1 Start Date 1st October 2026
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well as at CEH and UCL. For further information on the project, we will be hosting a ‘Prospective applicant webinar’ at 2:00pm on the 26th of November. Link to the event can be found here: https
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properties of representative sediment classes. · Evaluate methods for predicting sediment type and physical properties from geophysical data using machine learning. · Assess the reliability
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properties of representative sediment classes. · Evaluate methods for predicting sediment type and physical properties from geophysical data using machine learning. · Assess the reliability
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be hosting a ‘Prospective applicant webinar’ at 2:00pm on the 26th of November. Link to the event can be found here: https://events.teams.microsoft.com/event/376b2195-d8da-47c0-86e2-b18813ec19e3