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motivated post-doctoral associate with a strong background in control systems and machine learning to join the research team of Prof. M. Umar B. Niazi. The position focuses on the development of digital twins
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of quantum computing, quantum algorithms and complexity, quantum cryptography, quantum program verification, quantum machine learning, etc. * Within the predetermined research scope and methodology, conduct
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Institute for Machine Learning – the largest computer vision and machine learning research group in Australia – and contribute to world-leading research projects at the Centre for Augmented Reasoning
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automating geospatial workflows. Proficiency with GIS tools (e.g., QGIS, ArcGIS) for spatial analysis and visualization. Experience developing statistical or machine learning models to estimate fuel moisture
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, Computer Science, or Information Science. The position requires experience with at least one of the following: Data Science, Machine Learning, Computational Social Science, Big Data. Relevant skills could
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(completed or near completion) in Computer Science, Computer Vision, NLP, Machine Learning, Computer Graphics/Animation, HCI, or a related field. Strong background in deep generative modelling (diffusion
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or junior graduate students. A formal training, education, or certification in a secondary area (beyond the main PhD focus) such as additive manufacturing, advanced/hybrid manufacturing, machine learning
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(ongoing PhD project). These pre-screened datasets will then be analyzed by various machine learning techniques (dimensionality reduction, unsupervised clustering, artificial neural networks, auto-encoders
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adaptive robotic strategies. The work will involve the integration of: Advanced motion planning and control algorithms Multi-modal perception techniques (e.g., vision, tactile, force) Machine learning models
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design, and/or machine learning in the context of integrated photonics. We are looking for someone who wishes to work theoretically in this field, while still maintaining close contact with experiments