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The offer of an Industrial CASE award for a PhD studentship by AstraZeneca has provided an opportunity for an exciting PhD research programme on developing methodologies for predictive milling of organic solids at the Institute of Particle Science and Engineering, University of Leeds.
The overall aim of the project is to develop predictive milling of organic solids by analysing the prevailing dynamics (impact and shear stresses and strains) of particulate solids in a mill and the mechanical properties accounting for particle breakage.
The mechanical properties are to be characterised by the state-of-the-art nano-indentation and impact test facilities at the University of Leeds. Model development will be based on the Distinct Element method and population balance program of g-Solids (PSE Ltd).
The choice of mill to be analysed will be identified at the project start. The rationale for the proposed work arises from the need to develop predictive milling ability by using a small number of test particles, whilst taking account of environmental conditions, mill type and material properties.
How to apply:
Formal applications for research degree study should be made on-line through the http://www.leeds.ac.uk/students/apply_research.htm. Please state clearly on the funding section of the application form that you wish to be considered for the ‘Developing predictive milling of organic solids’ studentship. In the research information section please state the name Prof M Ghadiri.
Funding Notes:
This studentship, which is open to UK/EU in the first instance, will pay the academic fees at the EU/UK rate as well as providing an annual stipend of approximatley £13,590 per year plus an additional industrial contribution of up to £2000.
Applications are invited from candidates with or expecting a First or Upper Second Class Honours Degree (or equivalent) in engineering (Chemical Engineering, Mechanical Engineering, Materials Science & Engineering), physical sciences (Chemistry or Physics) or applied mathematics. Due to the nature of the project, a good level of competence in numerical methods and experimental skills are essential.
References:
In addition, communication and team-working skills are highly desirable due to the strong industrial link.