PhD Studentship - Bayesian geometric inverse problems
University of Nottingham - Mathematical Sciences
|Funding for:||UK Students, EU Students|
|Funding amount:||£14,296 stipend|
|Placed on:||10th November 2016|
|Closes:||7th February 2017|
Location: University Park
Supervised by Dr Marco Iglesias
This project will be based at the University of Nottingham in the School of Mathematical Sciences.
The aim of this project is to develop computational Bayesian techniques for the solution of geometric inverses problems that arise in a wide range of applications such as subsurface geophysics, manufacturing engineering and the built environment. Examples of geometric inverse problem that will be addressed with the techniques developed in this project are: (i) inference of fracture networks and/or conduits in Karst aquifers during the injection of CO2 for its geologic storage; (ii) detection of defects in reinforced preform during the resin infusion process in the fabrication of composite materials; (iii) inference of internal structures (e.g. cavities) in building structures such as walls with the aim of improving estimates of energy consumption. These problems have an underlying (forward) model described by Partial Differential Equation(s) (PDE) with input parameters associated to some (unknown) physical property of interest; the inverse problem is to infer this property from noisy observations of the solution of the PDE. In the context of problems (i)-(iii), sophisticated geometric parameterizations are often required to enable an accurate and realistic characterization of these properties (e.g. channelized structures in Karst networks). This project will develop computational hierarchical Bayesian methodologies to infer those geometry-constrained properties within an infinite-dimensional Bayesian framework for PDE-constrained inverse problems.
Depending on the applicant’s interest and academic background, the project could include the development of geometric parameterizations based on computer vision, image reconstruction and segmentation (e.g. level-sets) techniques; in this case, the project could be potentially co-supervised by Dr. Bai Li, Computer Science at Nottingham.
Summary: UK/EU students - Tuition Fees paid, and full Stipend at the RCUK rate, which is £14,296 per annum for 2016/17. There will also be some support available for you to claim for limited conference attendance. The scholarship length will be 3 or 3.5, depending on the qualifications and training needs of the successful applicant.
Eligibility/Entry Requirements: We require an enthusiastic graduate with a 1st class degree in Mathematics (or other highly mathematical field such as Physics and Computer Science), preferably at MMath/MSc level, or an equivalent overseas degree (in exceptional circumstances a 2:1 class degree, or equivalent, can be considered).
Apply: This studentship is available to start from September 2017 and remain open until it is filled. To apply please visit the University Of Nottingham application page: http://www.nottingham.ac.uk/pgstudy/apply/apply-online.aspx
For any enquiries please email: email@example.com
This studentship is open until filled. Early application is strongly encouraged.
Share this PhD
Type / Role:
Midlands of England