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Position: Advanced fluid bed reactor studies (linked to EPSRC Programme Grant PREMIERE)
Institution: University College London
Department: Department of Chemical Engineering
Location: London, United Kingdom
Duties: The research in the studentship will focus on the design and operation of gas-solid and liquid-solid fluidised beds mimicking those used in nuclear reprocessing. The student will carry out fluid dynamic and thermal studies in fluidised bed reactors at high temperature using high power pulsed X-Ray imaging and infrared thermography to determine the flow pattern inside the bed, heat transfer mechanisms and solid particle behaviour. The results will be compared with those from acoustic sensors, developed by other researchers in the project
Requirements: The candidate should have or expected to obtain a first or upper second class (or equivalent) degree in Chemical Engineering, Mechanical Engineering, or a related subject area. Prior research experience, together with the ability to analyse, develop and solve open-ended research problems is essential. Desirable qualifications include knowledge of particle technology and fluidization as well as previous experimental research experience
   
Text: Advanced fluid bed reactor studies (linked to EPSRC Programme Grant PREMIERE), - Ref:1867791 Click here to go back to search results UCL Department / Division Department of Chemical Engineering Location of position London Duration of Studentship 3.5 years Stipend £17,432 per annum UK/EU fees Vacancy Information Applications are invited for a PhD studentship in the Department of Chemical Engineering at UCL. The main role will be to carry out experimental investigations on multiphase fluid-bed systems. The studentship will be closely associated with the EPSRC Programme PREdictive Modelling with QuantIfication of UncERtainty for MultiphasE Systems (PREMIERE) to create the next-generation predictive framework for complex multiphase flow systems relevant to the energy, healthcare, manufacturing, and digital technologies sectors. The project brings together a multi-disciplinary team of researchers including leading academics in data-centric engineering, machine-learning, computational fluid dynamics, high-performance computing, and multi-scale experiments at Imperial College London, Birmingham, Cambridge, University College London, and the Alan Turing Institute. The successful candidate is expected to supervise undergraduate students and to interact in a multi-disciplinary environment. The post holder is required to write up the results for reports and journal publication, and present them at conferences. Studentship Description The research in the studentship will focus on the design and operation of gas-solid and liquid-solid fluidised beds mimicking those used in nuclear reprocessing. The student will carry out fluid dynamic and thermal studies in fluidised bed reactors at high temperature using high power pulsed X-Ray imaging and infrared thermography to determine the flow pattern inside the bed, heat transfer mechanisms and solid particle behaviour. The results will be compared with those from acoustic sensors, developed by other researchers in the project. Please apply here: https://evision.ucl.ac.uk/urd/sits.urd/run/siw_ipp_lgn.login?process=siw_ipp_app&code1=RRDCENSING01&code2=0029 Person Specification The candidate should have or expected to obtain a first or upper second class (or equivalent) degree in Chemical Engineering, Mechanical Engineering, or a related subject area. Prior research experience, together with the ability to analyse, develop and solve open-ended research problems is essential. Desirable qualifications include knowledge of particle technology and fluidization as well as previous experimental research experience. Eligibility The post is open to UK/EU citizens only. Contact name Prof Paola Lettieri Contact details p.lettieri@ucl.ac.uk UCL Taking Action for Equality Closing Date 15 Aug 2020 Latest time for the submission of applications 23.59 Interview date TBC Studentship Start Date October 2020 untitled
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