El 1 (S&t Level 5) - Ai/ml Researcher for Adaptive
3 days ago
$106,074 - $119,651 (plus Super)
- Edinburgh - SA
**The Role**
As an AI/ML Researcher for Adaptive Situational Awareness and Decision Making, your role is to integrate advances in these techniques, especially deep learning, toward achieving effective situation awareness and facilitating robust decision making in uncertain, dynamic and adversarial contexts.
Some of your key responsibilities include:
- Contribute to R&D activities, in collaboration with academic partners, toward endowing a deep learning model an ability to evolve in uncertain, rapidly changing contexts; including addressing the multi-modal time series anomaly detection and forecasting tasks using self-supervised and continual learning (or similar) approaches.
- Contribute to R&D activities, in collaboration with academic partners, toward domain-adaptive event extraction from multi-modal unstructured data, to support Defence client requirements, including situational awareness and sensemaking to decision makers in multi-domain operations.
- Contribute to the development of proof-of-concept and prototype demonstrators.
- Communicate, publish and report findings in the Defence and scientific community.
AIDA are also advertising for a S&T 4 'AI and Data Scientist position. Please click here for more information.
**About our Team**
The Artificial Intelligence for Decision Analytics (AIDA) STC undertakes advanced analytics for machine-enabled planning, situation awareness and decision-making. The STC comprises two S&T disciplines: Situation Representation and Analysis (SRA), and Adaptive Artificial Intelligence (A2I).
The A2I discipline focused on AI/ML techniques that can rapidly adapt to changing, uncertain and adversarial contexts, and be quickly adapted to tasks across domain and environments, toward enabling and enhancing adaptive situational awareness and decision making.
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Highly desirable:
- Experience with handling complex optimisation problems and deep representation learning.
- Experience with self-supervised learning, and learning with 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.
Desirable:
- Experience with programming languages, especially Python
- A track record of publications is desirable.
- Sound inter-personal skills and experience working effectively in multi-functional teams.
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