VACANCY INFORMATION
The UCL Department of Chemical Engineering is one of the top research and teaching departments in the UK and has world-class standing. The department offers undergraduate and postgraduate programmes and has an extensive research portfolio across a wealth of areas, from the molecular scale to the scale of industrial plants. It hosts 27 academics whose research is collaborative, ground-breaking and focused on solving societal problems.
The Chemical Engineering Department is seeking an enthusiastic and dedicated Ph.D. student to research mass transfer in pharmaceutical processes at different scales and develop advanced Computational Fluid Dynamics (CFD) models for predicting solid-liquid and liquid-liquid mass transfer coefficients. This project is in collaboration with GlaxoSmithKline, a global pharmaceutical company with strong focus on research and development (R&D). The post-holder will have the opportunity to share ideas and results with the industrial partner and collaborate with its R&D team.
Understanding of multiphase flows and numerical codes for multiphase simulations is desired - but not essential - as it will be developed during the project.
The post is fully funded (stipend and fees) for 3.5 years.
STUDENTSHIP DESCRIPTION:
Many pharmaceutical processes for the preparation of drugs involve heterogeneous reactions. In some cases, reaction rates are limited by mass transfer of reactants between the phases; thus, the process performance may depend on the equipment and scale-up issues may result. Similar issues arise in crystallization processes.
Mathematical modelling is becoming a critical tool for addressing this challenge and aiding the development of digitalized process solutions. Detailed first principle and mechanistic models can offer insight into the stages of a process and drug substance development, an essential support for optimizing current and upcoming processes. Modelling mass-transfer-limited processes is possible only if mass transfer coefficients are known. This poses a problem, because estimating them experimentally is extremely challenging and their values depend on the scale of the equipment. This problem can be overcome with CFD models, which can predict mass transfer coefficients at scale and without the need for extensive experimental campaigns. This is precisely the aim of this project: investigating mass transfer in pharmaceutical processes at different scales and developing advanced CFD models for predicting mass transfer coefficients.
The post-holder will learn how to use multiphase CFD codes and post-process and interpret the results of the simulations, which will be validated against experimental data. The techniques and skills (s)he will learn are transferable to technological problems relevant to several industrial sectors, e.g., healthcare and catalysis.
The post-holder will present the research results at international conferences and in peer-reviewed journal articles of high international standing.
PERSON SPECIFICATION
The successful candidate will have completed a first-class degree at the MEng or MSc level in Chemical or Mechanical Engineering, Physics or a related discipline.
The successful candidate will be a dedicated student, preferably with advanced understanding of transport phenomena and research methods.
Willingness to perform independently, yet within a collaborative environment, is a must.
Demonstrable knowledge of research methods and Computational Fluid Dynamics simulations is desirable but is not a necessary requirement.
ELIGIBILITY:
First-class degree at the MEng or MSc level is required.
Funds are available to cover UK, EU as well as Overseas fees.
EU and Overseas students are eligible (the scholarship will cover their fees in full).
The successful candidate is expected to start in 01/10/2021
To discuss this position please email Dr Luca Mazzei: [Email Address Removed]
To apply, please submit you application through the following link (specifying Luca Mazzei as academic supervisor and including a statement of interest): https://www.ucl.ac.uk/adminsys/search/
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