About the Project
This collaborative research project between the University of Edinburgh (UoE) and a major multinational pharmaceutical company will employ high-fidelity numerical modelling to capture, simulate, visualise and optimise the design and operation of high-value Active Pharmaceutical Ingredient (API) manufacturing flowsheets at high Process Mass Intensity (PMI), towards the sustainable and environmentally benign production of medications.
Viable API production intensification is feasible by reducing solvent usage, yet ensuring stably (e.g. no clogging) efficient unit operations is the resulting challenge. More efficient batches at lower solvent inventory reduce waste for higher throughput and profitability. The purpose of this PhD project is to assess in silico the effect of solvent choices, flowsheet configuration (process synthesis) and inventories on API plant efficiency: this can be a game changer, using a unified framework of rigorous kinetic parameter estimation and separation thermodynamics. Industrial placement and collaboration form an integral part of this project.
The Gerogiorgis Research Group at the School of Engineering (University of Edinburgh) employs high-fidelity first-principles modelling and advanced numerical methods for systematic synthesis, design and optimisation of complex chemical processes, with emphasis on continuous pharmaceutical manufacturing and comparative technoeconomic analyses for pharmaceuticals, bioproducts, food/drinks and energy. Their research is recognised with multiple IChemE Global Award distinctions, the Academy of Athens Loukas Moussoulos research publication prize, and two Industrial Fellowships from the Royal Academy of Engineering (RAEng) and the Royal Society (RS).
Applications will be accepted until 30th June 2021 however may close early if a suitable applicant if found.
The University of Edinburgh is committed to equality of opportunity for all its staff and students, and promotes a culture of inclusivity. Please see details here: https://www.ed.ac.uk/equality-diversity
An advanced undergraduate degree (MEng or Dipl. Eng.) in Chemical Engineering (2:1 or higher, 1st class preferable), with substantial prior (Dipl./MEng thesis) research experience, is required. Strong numerical modelling and coding (e.g. MATLAB) skills are essential; process simulation and optimisation skills (e.g. proficiency in using gPROMS/ASPEN/UNISIM) are important for this PhD project.
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