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Offer: PhD Position: Improved Journal Bearing Performance Prediction via the use of Machine Learning:Job description:Qualification Type: PhD Applications are invited for PhD studentships to conduct thin film fluid dynamics research into the use of machine learning techniques for thermo-elastic hydrodynamic lubrication (TEHL) modelling. The project aims to simulate, understand, characterise and model the performance of a journal bearing via predictive machine learning models. This will be achieved by the use of existing journal bearing models, that have been developed at the University of Nottingham, to create a large database of solutions which will be used as the input to develop predictive machine learning techniques. Experimental validation data will be available from continuing separate projects. During the project the candidate will gain practice in the use and development of numerical modelling, data analysis, Thermofluids analysis, coding and machine learning techniques. The applicant appointed will join the University of Nottingham's Gas Turbines and Transmissions Research Centre (G2TRC), home to the Rolls-Royce University Technology Centre in Gas Turbine Transmissions Systems. They will join a team of around 50 researchers, academics, engineers and technicians working on a variety of aero-engine transmission, energy and fluid system related projects. We are seeking for an enthusiastic and self-motivated person who meets the academic requirements for enrolment for PhD research at the University of Nottingham. Ideally you will have a 1st class or good 2:1 honours degree in a significant engineering or related subject, and an enquiring and rigorous approach to research together with a strong intellect and disciplined work habits.A good expertise or practice in fluid mechanics and numerical modelling is highly desirable. As development of machine learning models will be required during the project, practice in coding is also highly desirable (Python or C++). Good team-working, flexibility and communication expertise are all essential expertise for the prosperous candidates. The PhD position is available from 1st October 2022. The funding is for UK/eligible for home fees students only. This project will include the payment of tuition fees as well as a stipend equivalent to RCUK rates (currently at £15,609 p.a. tax free for 2021/22) awarded to the appropriate candidate. When applying for this studentship, please include the reference number (beginning ENG) within the personal statement section of the application. This will help in ensuring your application is sent directly to the academic advertising the studentship. Informal enquiries may be sent to Dr Benjamin Rothwell (Benjamin.Rothwell@nottingham.ac.uk). Please apply here https://www.nottingham.ac.uk/pgstudy/how-to-apply/apply-online.aspx The University actively supports equality, diversity and inclusion and encourages applications from all sections of society. Skills:
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