First listed on: 06 January 2022
Artificial Intelligence and Machine Learning Specialist


EL 1 (S&T Level 5)
$106,074 - $119,651 (plus Super)
Edinburgh - SA

The Role
The Joint and Operations Analysis Division (JOAD) is seeking an experienced researcher in Artificial Intelligence (AI) and Machine Learning (ML) who is passionate in applying state-of-the-art AI and ML methods toward addressing novel problems with Defence and national security impact.

As an AI & ML Specialist (applied research scientist), you will have opportunities to engage with expert multi-functional teams in Defence and working in close collaboration with industry and academia; leading R&D activities to tackle challenging real-world problems; and publishing some results. More specifically, your role is to develop and integrate advances in techniques (especially deep learning) toward achieving effective situation awareness to facilitate decision making in uncertain, dynamic and adversarial contexts.

This role sits within the Adaptive Artificial Intelligence (A2I) discipline of the Artificial Intelligence and Decision Analytics (AIDA) Science and Technology Capability (STC) in the Joint Warfare and Operations (JWO) Major Science and Technology Capability (MSTC) of JOAD.

Some of your key responsibilities include:

  • Work in collaboration with Defence and DSTG stakeholders to identify challenges and opportunities for the application of AI and ML.
  • Conduct R&D activities toward addressing challenges of modelling events and activity patterns from large volumes of heterogeneous multimodal time-series data, as well as handling intrinsic noise and uncertainty in data.
  • Develop AI and machine (deep) learning algorithms and modelling techniques toward detection, recognition, characterization and forecasting of events, activities and behaviours of Defence interest.
  • Contribute to the development of proof-of-concept and prototype demonstrators.
  • Communicate, publish and report findings in the Defence and scientific community.

About our Team
The JWO MSTC provides definition, representation and modelling of enterprise and capability systems from a whole-of-system perspective, applied to complex operational capabilities. The MSTC focuses on delivering science and technology (S&T) to mitigate operational risk and create a warfighting edge. The MSTC enhances and supports planning, preparation, and employment of the integrated joint force in current and future operations, thus enabling the ADF to achieve a capability edge in decision making at the strategic and operational level.

JWO nurtures the required multidisciplinary knowledge and skills in four S&T groups: Artificial Intelligence for Decision Analytics (AIDA), Command and Control Information Systems, Influence and Conflict Analysis, and Theatre Operations Analysis. The AIDA undertakes advanced analytics for machine-enabled planning, situation awareness and decision-making. The STC comprises two S&T disciplines: Situation Representation and Analysis, and Adaptive Artificial Intelligence.

Our Ideal Candidate
JOAD is seeking a research scientist with degree qualifications and/or demonstrated experience in relevant areas of Data Science, Machine Learning and/or Artificial Intelligence. In addition, the ideal candidate will demonstrate some of the following:

Highly desirable:

  • Experience with deep representation learning, including representation learning with graph data, and learning in the presence of limited amount of labelled data.·
  • Experience in handling complex, high-volume, high dimensionality data from varying sources.
  • Fluency in state-of-the-art machine learning frameworks such as TensorFlow and PyTorch.


  • Experience with programming languages such as Python, Java, C++ and others. Experience with more than one language is preferred.
  • A strong track record of publications is desirable.
  • Sound inter-personal skills and experience working effectively in multi-functional teams.

Application Closing Date: Thursday 03 February 2022

For further information please review the job information pack, reference DSTG/07151/21 on


Recent Jobs