PhD opportunity: Curtin University (machine learning)

Applications close:  
October 14, 2022

PhD opportunity: Curtin University (machine learning)


Curtin Institute for Computation


Xsights is searching for an outstanding research student based at Curtin University to undertake an industry-based PhD focusing on the development of new machine learning approaches and applications within the agricultural technologies domain.

The research student will design, develop, implement, and evaluate machine learning models and architectures based on physiological data used to assess animal health and welfare and utilise these measures to identify abnormalities, predict adverse outcomes, and accommodate other applications of value.

This is a high-profile, industry-based research collaboration concerned with developing scalable digital solutions for the agricultural industry to support data-driven decision making and enhance day today livestock management.

The selected student will be afforded the opportunity to engage with multiple key stakeholders including Xsights, Food Agility, the Curtin Institute for Computation, and the Craig Mostyn Group to utilise research to drive the development of impactful products which solve significant real world problems through the lens of academic frameworks.

This is an excellent opportunity for a motivated research student with a passion for machine learning and its application within the broader application development space to utilise their expertise to support the creation of transformative digital solutions whilst also providing significant contributions to the broader research community.

Scope of research work and outputs

  • Machine learning models, architectures, and frameworks which enable the health and welfare of livestock animals to be predicted based on physiological data. This would include the ability to detect variations inactivity, feeding, and health as well as the provision of data-driven rules which identify healthy animals separate from those in decline.
  • The chosen approach should generalise well to accommodate related opportunities and domains of interest where livestock and physiological data is concerned.
  • Framework for identifying correlations and entities of interest from ingested data autonomously. Working with the technical team, support the development of a framework for ingesting data and training and deploying machine learning models at scale.
  • Working with the technical team, support the development of a framework for ingesting data and training and deploying machine learning models at scale.
  • Working with the product and technical teams, support the implementation of trained machine learning models within a commercial solution context with an emphasis on reporting and surfacing insights and predictions in a way that has utility and impact for end-users.
  • All necessary implementation guidelines and documentation.
  • Multiple peer-reviewed publications in high quality journals and the ability to present work at conferences.
  • There are considerable career-development opportunities for industry-based internships throughout the student’s candidature.

Student learning and professional development outcomes

  • Understanding of and ability to develop machine learning artefacts that are accurate, reliable, and scale effectively.
  • Ability to evaluate and refine models with reference to baseline data, as well as proficiency with approaches for updating and enhancing models as new data becomes available.
  • Familiarity with physiological data, including necessary pre-processing challenges and contingencies for supply chain development.
  • Ability to understand and work towards commercial outcomes and imperatives in a reporting-intensive environment through the application of collaborative research.


  • The total dollar value of the stipend: $35,000 per annum (tax free). This is for a stipend only. Successful HDR applicants for admission may receive a 100% fee offset for up to four years.
  • Duration of the scholarship: Three years
  • Stipend only commences whilst student is onshore.

How to Apply

Apply by
October 14, 2022
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Curtin University in Perth, Western Australia

For more information contact

Dr Elizabeth Jackson, (for questions about the broader project)

Professor Melanie Johnston-Hollitt, (for questions about the science and technical aspects of project)

Dr Michael Garrett, (for questions about the project’s industry partner and technical aspects of project)

Candidate Criteria

  • The successful candidate must be able to commence full-time studies on location at Curtin University in Perth, Western Australia, no later than Monday, 30February, 2023. There is no negotiation on this.
  • Background in data science, mathematics, physics or related field with an interest in machine learning design and methodologies.
  • Proficiency with programming languages such as Python, R, Java, C/C++, Julia, etc. and the ability to develop prototype applications for testing and validating ideas and approaches. Experience with large scale data storage and analysis and/or software development will be an advantage.
  • Outstanding oral and written communication skills, particularly for technical projects.
  • Genuine interest in collaborative research and working on research projects that support the development of new commercial software solutions which emphasise data-driven insights.
  • Ability to engage with multiple stakeholders and collaborate effectively within a broader multidisciplinary team.