Combined experimental and numerical study of powder flow during pharmaceutical manufacturing
The project aims to understand the flow of powders during pharmaceutical manufacturing and to design and optimise the feeding system, building upon recent research and the facility developed at the University of Surrey.
Start date1 October 2020
Tuition fee at the Home/EU level (i.e. £4,327 per year) and a stipend of £15,009 per year.
Start date 1 October 2019: Applications accepted all year round until the position is filled.
Funding sourceUniversity of Surrey matched PhD funding and financial support from Genentech Inc.
We are looking for a talented candidate to work on a PhD project in collaboration with a pharmaceutical company based in San Francisco, California, USA.
Around 80% of medicines are in the tablet form that are manufactured by compression of dry powders. Understanding the flow of powders during the manufacturing process is critical to improve manufacturing efficiency and product quality.
Working with a research intensive pharmaceutical company, this project aims to design a lab-scale experimental system to mimic the tabletting systems. The developed apparatus to investigate optimal pharmaceutical formulations and their flow behaviours during tabletting. Furthermore, the powder flow behaviour during the manufacturing will also be investigated numerically using the discrete element method, which will also be used to optimise the process system and predict powder flow behaviour during manufacturing.
Candidates should have a good degree in Engineering, Pharmaceutics, Materials science or a related discipline.
Applications from UK/EU Students only.
IELTS Academic: 6.5 or above (or equivalent) with 6.0 in each individual category.
Research group: Formulation and Product
Our aim is to develop science-based predictive models, design tools and innovative manufacturing processes for formulated products. This is underpinned by our active research in particulate materials manufacturing, multiphase flow, advanced numerical modelling using coupled discrete element methods with computational fluid dynamics (DEM-CFD) and finite element modelling (FEM), process modelling and optimisation, and measurements and characterisation using advanced techniques such as x-ray computed microtomography, and positron emission particle tracking (PEPT).