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Research Associate in Reduced Order Modelling for Carbon Capture

University of Sheffield

Sheffield, United Kingdom

Summary: Chemical and Biological Engineering is a thriving department within the University’s Faculty of Engineering, comprising 34 academic staff, 41 research staff and technicians, 11 support staff and over 500 undergraduate and postgraduate students. The Department has a vibrant research and teaching culture spanning particle science and technology / nanotechnology, new energy technologies, the environment and applications of post-genomics bioscience for biotechnology and bioprocessing applications. We're ranked amongst the UK's top five Chemical Engineering departments for world leading and internationally excellent research and ranked number one for research environment based on the results of our Unit of Assessment in the Research Excellence Framework 2014. The successful candidate will be under the direct supervision of Dr Solomon Brown and will look at Reduced Order Modelling (ROMS) for Carbon Capture systems. The project is part of an ambitious £6.2 m research program in support of the UKCCSRC 2017 involving major Universities across the UK, including Imperial College, University of Cambridge, University of Edinburgh.

The aim of the project is to use ROMS to bridge technology and system scales to facilitate the use of process models for accurately simulating Post-Combustion Capture (PCC) operations within wider system-level assessments, while mitigating the prohibitive computational burden imposed by their direct use. As part of this role the Research Associate will liaise with partner institutions working at either length scales to specify key performance indicators of the systems under study. The Research Associate will also develop and implement a robust ROM methodology for application to the range of possible capture technologies and collaborate in the implementation of these models at system scale. It is essential that the successful candidate have a good PhD in a relevant discipline and have experience in reduced order modelling of complex systems along with experience of development and application of computational software, ideally Python. It would also be desirable that the successful candidate had experience of working in collaboration with multiple external institutions and have a record of high quality research publications.


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