Closing date: 30 July 2019
Subject areas: Engineering
Start date: October 2019
Project description: Complex large-scale dynamical system often has a vast number of degrees of freedom. It is not possible to model the system sufficiently quickly to predict behaviours in real time. This project will extract effective data to construct a fast model using deep learning methods. Deep learning is part of a broader family of machine learning methods and has been applied to a number of fields.
The proposed PhD project offers the unique opportunity to develop a data-driven reduced order model (ROM) using deep learning methods. It provides a fast way of performing computationally intensive tasks with real-time speed for fluids problem. The proposed new ROM is constructed from a number of simulations representing different parameters such as different initial or boundary conditions. The deep learning methods are used to extract features from those simulations. After constructing the ROM, it is able to run the simulations with several orders of magnitude speedup.
Project supervisor: Dr Dunhui Xiao
For more details please see here: https://www.swansea.ac.uk/postgraduate/scholarships/research/engineering-centenary-phd-new-generation.php
Candidates should hold a first class honours degree and/or distinction at Master’s level in Computational mathematics, statistics, computer science, physics, or engineering.
Knowledge or experience of machine learning and fluid dynamics is an advantage (but not essential). Programming skills are essential.
We would normally expect the academic and English Language requirements (IELTS 6.5 or equivalent) to be met by point of application. For details on the University’s English Language entry requirements, please visit http://www.swansea.ac.uk/admissions/english-language-requirements/
To apply, please complete and submit the following documents to Dr Dunhui Xiao (email@example.com):
- College of Engineering PGR Scholarship Application
- Two page CV
- Degree certificates and transcripts
- One page cover letter
- Contact details of at least two referees for letters of recommendation
International applicants may apply, but the funding source to cover the fee difference must be guaranteed and detailed in the covering letter and an IELTS result of 6.5 must be submitted.
For enquiries please contact Dr Dunhui Xiao (firstname.lastname@example.org).
The scholarship covers the full cost of tuition fees and an annual stipend for UK/EU candidates but tuition fees only for international candidates.
UK/EU candidates: The scholarship covers the full cost of UK/EU tuition fees and an annual stipend of £14,296.
International candidates: The scholarship covers the full cost of tuition fees only.
There will be additional funds available for research expenses.