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Quantitative NMR using Bayesian analysis

   Chemical and Process Engineering

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  Assoc Prof Daniel Holland  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

Nuclear Magnetic Resonance (NMR) is one of the most commonly used analytical techniques in chemistry. Traditionally NMR relies on the use of large, superconducting magnets and very high magnetic field strengths in order to distinguish between different molecular species. Recently, new NMR instruments have been developed that use permanent magnets and hence are much cheaper and more compact than superconducting NMR instruments. These new devices open up opportunities for entirely new applications of NMR, especially with regard to quality control and investigation of chemical processes. However, the sensitivity of these instruments is not sufficient for many applications. We have recently developed a mathematical technique to enhance the effective sensitivity of NMR. The new approach uses Bayesian statistics to fully exploit our prior knowledge of the samples to be studied.

During this project, we will collaborate with Magritek, the world’s leading manufacturer of permanent magnet NMR devices, to develop and implement our proposed algorithm on these permanent magnet devices. The project will focus on the development of the algorithm, but will also require an element of experimental work. The successful applicant will be expected to work with our partners at Scion in Rotorua, who are developing sustainable or green feed stocks for chemical engineering, and our partners at the University of Kaiserslautern in Germany, who are developing novel industrial measurement techniques using NMR.

To apply for this position or for more information about this project, please email [Email Address Removed], and enclose a copy of a recent CV, including a copy of your complete academic transcript. Applications will be assessed when received. Applications close on the 31st of January 2017, or when the position is filled.

Keywords: NMR, Bayesian, chemical engineering, signal processing, permanent magnet, green chemistry

We are seeking a self-motivated PhD applicant with an excellent academic record and strong written skills. The student will be expected to demonstrate outstanding ability in mathematics, whilst maintaining the pragmatic approach required to deal with real-world problems. The student will also need to demonstrate an aptitude to learn a range of new skills outside their existing discipline.

Applicants should hold an undergraduate degree (first or upper second-class), or an MSc/ME in engineering, mathematics or physics. Applicants will need to meet all requirements for enrollment in the PhD programme at the University of Canterbury.

Funding Notes

The successful applicant will receive a PhD project scholarship comprising an annual stipend of NZ$25,000 p.a. for 3 years, as well as payment of university fees. The project will be based in Christchurch, New Zealand which is on the edge of the Southern Alps. The University of Canterbury has a wide variety of clubs to make full use of the natural beauty of the surrounding environment. For further information about the university see
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