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Overview
Are you passionate about pushing the boundaries of supramolecular systems chemistry?
This interdisciplinary PhD in Chemistry will explore how to read out information from dynamic chemical systems. You’ll work at the intersection of analytical chemistry, data science, and synthetic chemistry, contributing to a transformative approach to supramolecular systems chemistry.
This project is part of our broader research effort to develop synthetic chemical systems that mirror behaviours of biological networks. By integrating advanced ion mobility mass spectrometry and machine learning, rather than simplifying complexity, we embrace it, transforming rich chemical interactions into a new frontier for systems chemistry.
Objectives
- Develop high-throughput experimental workflows, including using robotic systems and microfluidics.
- Use ion mobility mass spectrometry to monitor changes in synthetic chemical reaction networks.
Candidate
We’re looking for a motivated and curious candidate with a background in one or more of the following areas:
- Analytical chemistry or physical chemistry
- Mass spectrometry
- Synthetic Chemistry
- Data science or machine learning applied to chemistry
- Automation or robotics in laboratory settings
Prior experience with ion mobility mass spectrometry or machine learning applied to chemical datasets is advantageous but not essential, training will be provided.
How to Apply.
To apply, please first check "Determine Your Eligibility" here to assess your eligibility for entry to a PhD program at UNSW Sydney, including English language requirements. If you'd like to apply, please express your interest by submitting your CV, and a 1-page statement of interest letter to Dr Rijs (n.rijs[at]unsw.edu.edu). Informal inquiries are welcome and can be directed to Dr Rijs.
This position is fully funded for 3.5 years, including tuition fees and a competitive stipend.
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