We are recruiting for an exceptional Doctoral (PhD) Candidate to join the new MSCA Doctoral Network FairCFD (https://www.imft.fr/faircfd/project-presentation/). The candidate will enrol for a PhD in Chemical Engineering at the University of Cambridge, under the supervision of Prof. Andy Sederman.
FairCFD offers a unique opportunity to engage in experimental research linked to computational fluid dynamics (CFD) and more broadly engaging with scientific computing. The postholder will benefit from a unique breadth of experiences including:
* Contribute to technological innovation in health/food industries by developing advanced and efficient data measurement strategies.
* Join a vibrant network of 15 doctoral candidates, across 9 European countries, with access to network events, high-level training to technical and transverse skills, and secondments in both academic and industrial environments.
* Take part in a network-wide interdisciplinary effort to define and promote numerical sustainability in scientific research.
Flow MRI (magnetic resonance imaging of flowing fluids) is a non-invasive imaging technique that measures 3D and time resolved velocity fields in opaque fluids, making it uniquely valuable for studying flows under realistic operating conditions in a range of engineering and medical applications.
Recent advances in acquisition strategies and model based data assimilation improve the ability of Flow MRI to be used not just to visualise flow but to infer rheological behaviour directly from experimental data. This project will develop these capabilities by combining high information content Flow MRI datasets with physics based modelling and Bayesian inference to determine constitutive models for non-Newtonian and other complex fluids in situ. The project will require development of advanced experimental and data analysis skills and will work closely with the Doctoral candidate working in Cambridge on data assimilation (https://www.imft.fr/dc10-arterial-circulation/).
The objectives of the proposed study are to (i) design and run Flow MRI experiments on a range of non Newtonian fluids in steady and periodic flow (ii) develop and optimise MRI acquisition strategies to improve the efficiency of data collection and enhance spatial and temporal resolution (iii) increase the quantitative accuracy of Flow MRI data through improved reconstruction, and uncertainty estimation and (iv) assess the ability to accurately model these complex fluids by using adjoint accelerated Bayesian inference with the experimental Flow MRI data.
The implementation of new Flow-MRI acquisition and reconstruction strategies will enable measurement of flows at greater resolution and fidelity than has been possible previously. These new capabilities will be used to investigate applications that have not previously been possible including the healthcare sector (blood flow in hearts and arteries) and to assess rheology models in process fluids and foods.
The project involves secondments at the KTH (Stockholm, Sweden) and the University of Salerno (Salerno, Italy).
Applicants for the studentships must have a First Class (or a high 2:1) or equivalent degree in a relevant discipline such as chemical engineering, engineering or physics and must not have spent more than 12 months in the UK for the past 3 years.
Please see further information about the programme at https://www.imft.fr/faircfd/project-presentation/.
The successful candidate would be employed as a Research Assistant and they must apply for admission as a PhD student with the University and be able to meet our criteria for admission. For further information please visit: https://www.postgraduate.study.cam.ac.uk/courses/directory/egcepdcng.
Fixed-term: The funds for this post are available for 3 years in the first instance.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
As per MSCA Agreement.
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