First listed on: 30 September 2022
EL 1 (S&T Level 5) - Senior Researcher – Platform Systems

 Prognostics & Health Management
$108,195 - $122,044 (plus Super)
Fishermans Bend - VIC

The Role
Under broad direction, the Senior Researcher will work as part of a multi-disciplinary team undertaking research into prognostics and health management (PHM) condition monitoring capabilities to improve the readiness and availability of Defence military platform systems. 

They will develop and use various analytical tools to monitor complex mechanical and other systems, including gas turbine engines and propulsion gearboxes. The researcher will undertake the analysis of time-series sensor data, and the development of physics-based models of complex systems.

They will also employ data-driven digital engineering concepts including machine learning, deep learning, data visualisation and knowledge discovery techniques. The researcher will work closely with experts across DSTG and the broader S&T enterprise to develop, test and assess novel PHM concepts for Defence applications; ensuring they can operate optimally in military environments. 

Duties and Key Results Areas:

  • Work within a multidisciplinary team to develop, test and transition novel PHM capabilities to support improved readiness and availability of Defence platforms;
  • Engage with academic and industry partners in the development and transition of advanced PHM capabilities, building sovereign Australian capability to meet Defence needs;
  • Document and clearly communicate complex technical results and their implications to Defence stakeholders and external partners; and
  • Contribute to maintaining a positive, inclusive and respectful culture within diverse and multi-disciplinary teams (gender, cultural, age, religious and sexual diversity).

About our Team
Platforms Division aims to leverage world-leading science, technology and partnerships to deliver game-changing capabilities for Australia now and into the future. Aerospace Materials (AM) is one of several Branches comprising Platforms Division.

AM is primarily concerned with the deployment of materials in Aerospace platform and weapon systems, but also supports National Security, Land and Maritime domains. Our staff and partners provide diverse expertise in materials (functional and structural), advanced manufacturing & processing, advanced sensing, and computational materials modelling. Materials is a rapidly changing, enabling capability for a wide range of Defence challenges.

To ensure impact, the culture in AM is very collaborative, both within DSTG and the broader S&T ecosystem. AM’s five Groups cover many aspects of an Aerospace systems life cycle – from modelling & experimentation to support both acquisition and capability enhancement, manufacturing and lifting support for sustainment during operational life, through to planned withdrawal. 

The Prognostics and Health Management (PHM) group conducts innovative research in diagnostics, prognostics and health management technologies and applications, including physics-based and data-driven approaches for platform health management decision support.

The team consists of multidisciplinary and diverse backgrounds, and works to enhance platform readiness and safety in the Australian Defence Force (ADF). We closely engage with our Defence stakeholders and external partners, including academia, industry and international allies:

  • To collaboratively explore the strategic problem space and requirements,
  • To remain abreast of disruptive technologies, and
  • To provide novel solutions with impact to the ADF.

Our Ideal Candidate
Minimum of Bachelor Degree in a relevant technical discipline, such as Mechatronic/Mechanical/Aerospace Engineering, Computer Science, Applied Mathematics, and Physics; and possess some of the following attributes:

  • Demonstrated knowledge and/or experience in the analysis of time-series data using signal processing techniques;
  • Demonstrated knowledge and/or experience in the development, testing and application of Neural Networks, Machine Learning or Deep Learning algorithms;
  • Demonstrate knowledge and/or experience in modelling the dynamics of complex mechanical systems;
  • A high level of proficiency in one or more of the following: Matlab, LabView, Solidworks, Python, Tensor Flow and/or PyTorch;
  • Familiarity with Defence military platforms and platform systems maintenance concepts;
  • Excellent collaborative skills with a demonstrated ability to work within multidisciplinary teams including partners and stakeholders;
  • An ability to engage with experts with diverse technical backgrounds and facilitate interdisciplinary communication to enable development of solutions for complex tasks;
  • A demonstrated ability to grow and sustain positive relationships with team members and constructively participate in team and group activities;
  • Excellent written and oral communication skills and the ability to represent an organisation at a national level.

Application Closing Date: Thursday 27 October 2022

For further information please review the job information pack, reference DSTG/06342/22 on


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