PhD Scholarship - Energy Clustering

Last updated 1 hours ago
Job Type:Full Time

  • PhD scholarship opportunity with the UON and CSIRO
  • $28,092 plus yearly CPI increase
  • Additional Funding and Support available

The University of Newcastle is offering a PhD Scholarship in the field of Energy Clustering in collaboration with the CSIRO. The scholarship is suited to a PhD candidate who has undertaken studies in Statistics, Computational Statistics, Data Science, Computer Science, Mathematics, Engineering or a related field.

Project Title: Exploring Multifaceted Clustering of Complex Electricity Time-Series Data to Support Data-Driven Decision-Making in the Energy Sector

Project Details: The primary goal of this project is to explore methodologies and processes available for clustering complex, long, low frequency time series with spatial, temporal, or categorical factors associated with them - such as those found in the energy sector. The focus will be on mapping out which tools are most appropriate for use, the various considerations that should be made when using those tools, the metrics that should be used in validating their success and, when applicable, possible amendments/adjustments and improvements that may be required depending on the application scenario in hand.

Location: Newcastle, NSW (other locations may be considered)

Scholarship: $28,092 per annum over 3.5 years, plus Additional Funding and Support is available (please refer to UON advertisement)

Reference: 67639

Pre-Requisites/Eligibility Criteria

To be eligible to apply you must meet the following criteria.



Programming skills
Solid statistics/mathematics and/or computational background

Contact: For more information please contact Prof. Ricardo J. G. B. Campello, by phone (02) 4921 6762 or Email

How to Apply:

Applications should be sent to Prof. Ricardo J. G. B. Campello from The University of Newcastle. For details on how to apply, please see The University of Newcastle website at

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Applications close: Applications will close when a suitable candidate is found, therefore early applications are strongly encouraged.