PhD Research Scholarship Opportunity in NMR analysis of illicit drugs

We’re looking for a highly-motivated PhD applicant to join our multi-disciplinary team, to work on developing a field-invariant NMR spectroscopy database for the analysis of illicit drugs.

The project

Illicit drug use is a major cause of harm, particularly for young New Zealanders. Recent research has demonstrated that drug checking services can reduce the harm caused by illicit substances by providing users and agencies with intelligence about drugs in circulation, allowing for more informed decision making. In many cases, harm is caused because users inadvertently consume a different substance to that intended, or the dosage is different to that expected. For example, in early 2021, drug checking services such as Know Your Stuff and the Institute of Environmental Science and Research (ESR) identified eutylone being distributed as MDMA and were able to connect this with severe adverse reactions in users. Early identification enabled users to make informed decisions about whether to consume substances. However, existing drug checking services cannot provide quantitative information on the composition of substances, which is key intelligence to mitigate the risks of illicit substances. This project seeks to develop automated analysis of illicit substances using Nuclear Magnetic Resonance (NMR) spectroscopy.

NMR is a powerful analytical technique that provides both identification and quantification in a single measurement. Recently benchtop NMR instruments have become available that make NMR an affordable and accessible technique. The project is a collaboration between the University of Canterbury (UC), Victoria University of Wellington (VUW), and ESR. UC has developed a new analytical tool that uses quantum mechanical (QM) modelling of the NMR signature to enable accurate quantification of mixtures of substances using benchtop NMR. VUW provides expertise in machine learning for NMR applications. While ESR provides primary analytical chemistry and forensic services for the analysis of illicit drugs in New Zealand. We are now collaborating to develop a tool for the automated quantification and identification of illicit substances, including impurities and cutting agents, using benchtop NMR. This project will focus on developing machine learning techniques to enable automated analysis of compounds in the spectral database.

Requirements

The ideal candidate has a chemistry, data science, deep learning or chemical engineering Honours / Master’s degree. Knowledge of analytical chemistry, nuclear magnetic resonance (NMR), and Python are advantageous. However, we recognise it is unlikely any single applicant will have knowledge of all of the above, and we will provide training as required.

Funding and Opportunities

The successful applicant will receive a tax-free annual stipend of NZ$35,000 for three years, with additional funding to cover expenses such as tuition fees, Student Services Levy, consumables, as well as travel and accommodation costs for international conferences (if possible).

This project is hosted at the University of Canterbury, in collaboration with VUW and ESR.

For further information and to apply:

Please contact Professor Daniel Holland (daniel.holland@canterbury.ac.nz). Your cover letter, current CV, and undergraduate and postgraduate transcripts should be included in the application.