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Salary- $115,899 - $130,733 (+ 15% BDCP) + up to 15.4% superannuation
- Edinburgh - SA
The Role
Information Sciences Division (ISD) is seeking a candidate who is passionate about developing their skill sets in AI and Machine Learning (ML) and applying state-of-the-art techniques toward addressing novel problems with Defence and national security impact.
As a research scientist for Adaptive AI Planning for Cyber Operations, you will have opportunities to engage with expert multi-functional teams in Defence and work in collaboration with industry and academia. Your primary focus will be on developing and applying skillsets in adaptive AI and deep learning techniques toward supporting the automated generation of courses of action (COA) for planning and coordinating cyber operations. This will involve facilitating adaptive and robust decision-making across tasks, missions and environments.
You will demonstrate initiative, scientific integrity and pragmatism. You will be able to work with limited guidance within the context of the team’s objectives. You will have a demonstrated ability to recognise research challenges, pursue solutions, and communicate these effectively with stakeholders, team members and collaborators.
About our Team
This role sits within the Adaptive AI Planning (A2P) discipline of the Cyber Command and Control (CyC2) Science and Technology Capability (STC) in the Cyber Operations (CO) Major Science and Technology Capability (MSTC) of Information Sciences Division.
The main objective of the A2P discipline is to enhance decision-making agility, toward supporting cyber operations, command and control in complex, uncertain and adversarial environments. Specifically, A2P places a significant emphasis on machine-speed AI planning techniques and models that can evolve to adapt to rapidly changing situations, and that can be quickly adapted to diverse missions and tasks across domains.
The discipline's focus encompasses conducting research and development to harness and integrate advancements in AI and deep learning. This integration aims to facilitate real-world planning effectively, ensuring scalability and timely responsiveness — critical attributes for fostering effective and resilient cyber operations.
Our Ideal Candidate
The ideal candidate will exhibit interest and/or expertise in some of the following areas:
Highly Desirable
- Possess a solid background in one or more of the following fields: Computer Science, Mathematics, Statistics, AI and Deep Learning.
- Demonstrate experience in programming languages, especially Python.
- Demonstrate a strong interest in developing skill sets in one of the following areas: AI-driven planning and decision making, Markov Decision Processes (MDPs), Probabilistic and Statistical Modelling, or Deep Neural Networks.
- Display strong critical thinking and problem-solving skills.
Desirable
- Demonstrate an interest in developing knowledge and skill sets in cyber security.
- Have experience with popular machine learning frameworks such as TensorFlow and PyTorch.
- Demonstrate effective verbal and communication skills and an ability to work effectively with multi-functional teams.
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