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Mathematical analysis of a novel method of mineral fractionation
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Brief Outline:
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You
will work as part of a team led by Associate Professor Jeff Hogan and
Laureate Professor Kevin Galvin as part of the ARC 2020 Discovery
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.
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Detailed Description:
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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 the this new technology to produce
accurate washability data at low cost and with dramatically reduced
impact on human health and the environment.
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Eligibility Criteria:
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Applicants must
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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 under-represented groups are strongly encouraged
to apply.
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Degree Type:
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PhD only
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Application procedure :
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Applicants
should send a cover letter (including a statement of research interests
and suitability for the position, and contact details for two academic
referees), academic transcripts, and
CV to jeff.hogan@newcastle.edu.au Applications close 31 March 2020 or until the position is filled.
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Name of Supervisor:
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Associate Professor Jeffrey Hogan
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Expression of Interest deadline:
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31 Mar 2020 |