PhD Scholarship: Machine Learning-Enabled Processing - Melbourne, Australia - CSIRO

CSIRO Melbourne, Australia

3 days ago

Full time

Description

The Opportunity

Are you passionate about a career in research?
Want to work on cutting-edge research with a team of dedicated professionals?
Apply for this CSIRO-RMIT co-funded scholarship today

This CSIRO-RMIT co-funded PhD scholarship is available to conduct research into mineral resources.

The PhD candidate will gain intensive knowledge in innovative processing protocols for chemical sensing and to develop data acquisition system with the Machine Learning (ML) and/or Deep Learning (DL).

The successful candidate will have a unique opportunity to work closely with researchers and technical experts from CSIRO in a multi-disciplinary team environment. The project will provide numerous research and development opportunities including Cutting-edge chemical analytical and mineral characterization techniques: solution chemical sensing, mineralogy analysis, particle analysis, electron microscopy, and synchrotron technology.

The candidate should have experience in one or more of the following research areas: Chemical Engineering, Chemistry, Chemical Sensing, Environmental Science, Mineral Processing, Geochemistry

Project Title: Machine Learning-Enabled Processing and Visualization of Dissolved Metal Ion Sensing Data

Project Details:
In situ, real-time and continuous monitoring of leaching parameters, combined with thermodynamic simulation of leaching reactions, provides a comprehensive approach to fully define the bulk, surface, and solution species involved in mineral leaching and extraction processes. This data enables an improved understanding of the leaching mechanisms and kinetics.

Electrochemical sensors represent an important subclass of chemical sensors in which an electrode is used as the transduction element. They must be targeted for meeting the size, cost, and power requirements of on-site real-time monitoring. CSIRO Mineral Resources has developed a chronoamperometric method for the determination of Cu2+, Fe3+ and Fe2+ concentrations in leaching/bioleaching solutions for use with electrochemical sensors. The system needs further development and optimization.

This PhD Project will focus on providing a better understanding of the dissolved metal ion species present during the leaching of low-grade copper ores, and developing a real time data acquisition and self-recalibrating system for a long-life dissolved metal ion sensing technology using Machine Learning (ML) or Deep Learning (DL).

Location: Clayton, VIC
Scholarship: $33,000 per annum, plus a Tuition Fee Scholarship if required
Tenure: 3 years with a possible extension of six months
Reference: 87491

Eligibility:

To be eligible to apply you must have (or expect to gain):

have a first-class Honours or H1 or equivalent degree in a relevant discipline of engineering/science
be an Australian citizen, New Zealand Citizen or an Australian permanent resident or an international student meeting the minimum English language requirements
provide evidence of adequate oral and written communication skills
demonstrate the ability to work as part of a multi-disciplinary research team
meet RMIT's entry requirements for the PhD by research degree

International applicants must have the appropriate immigration approvals to allow them to take up the scholarship.

The successful applicant will be required to obtain and provide a National Police Check or equivalent.

Contact: For more information, please contact Dr Miao Chen on or via email at

How to apply:

You will be required to:

submit a Resume/CV and Cover Letter (as one document) in the 'Resume/CV' field which includes:
a research statement;
any publications/awards; and
the contact details of two referees.
upload your academic results in the 'Cover Letter' field.

If you experience difficulties applying online call and someone will be able to assist you. Outside business hours please email: csiro-

Flexible Working Arrangements
We work flexibly at CSIRO, offering a range of options for how, when and where you work.

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