You will work as part of a team led by Associate Professor Jeff Hogan and Laureate Professor Kevin Galvin as part of the AustralianResearch Council-funded project “Enhanced fractionation of mineral particles according to density". This is cross-disciplinary research involving the application of advanced mathematical techniques to a problem in particle separations, relevant to the resources industry.
In minerals processing, accurate resource assessment, plant design, and process assessment require knowledge of the mass distribution of the particles as a function of the particle density – the ``washability data’’. The traditional sink-float method has traditionally been used to obtain the data, utilising a series of baths containing liquids of different densities. There are, however, significant health and environmental problems associated with the sink-float method, not least of which being that the heavy liquids used are toxic, environmentally hazardous, and costly.
CI Galvin has developed new technologies for beneficiating particles in minerals processing, most notably the REFLUX™ Classifier used in gravity separation to separate particles according to their density using a water-based fractionation method. This project involves the development of an algorithm for the de-convolution of the fractionation data arising from this new technology to produce accurate washability data at low cost and with dramatically reduced impact on human health and the environment.
- have an excellent academic record in Honours in mathematics or a related discipline. Candidates with Masters by Research or Masters by Coursework degree are preferred.
- have a strong mathematical background.
- meet The University of Newcastle's entry requirements for the Doctor of Philosophy, including English language requirements.
- be willing to apply for internal and external travel grants and other available research support funding.
- be willing to work in both theoretical and laboratory environments, reflecting the cross-disciplinary nature of the research.
- be willing to travel to local and international research meetings.
Expertise in one or more of the areas of Harmonic Analysis, Optimisation, Numerical Analysis or Signal Processing is desirable. Programming skills in MATLAB or python are desirable.
Women and applicants from underrepresented groups are strongly encouraged to apply.
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Send a cover letter, academic transcripts, CV, statement of your research interests and suitability for this position, and contact details of two academic referees to firstname.lastname@example.org
Applications close 31 March 2020 or until the position is filled.