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together to provide autonomous discovery experimentation You will explore high through put experimentation through robots, nature of metal corrosion inhibitor interactions at a fundamental level and will
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You will explore the nature of metal corrosion inhibitor interactions through advanced molecular modelling and integrate this understanding into the formulation of evolutionary algorithms to discover new inhibitors. You will work with 3 world leading teams. You will explore the nature of metal...
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an ARC Linkage Project focused on developing an autonomous system for detecting and quantifying structural damage in infrastructures (e.g., bridges, grain silos) using computer vision, digital twins, and
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or autonomous operation. Supervision and Research Environment Lab: Design Health Collab, Faculty of Art, Design & Architecture, Monash University Lab Director: Professor Daphne Flynn PhD Supervisors: Dr Nyein
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Autonomous methods for fault or anomaly detection and classification of PV plants with high accuracy are necessary for the monitoring of large-size PV power plants. Objectives also include other
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for novel applications; user-focused testing; autonomous vehicles) Digital tools are ubiquitous in our homes, our workplaces, and across all aspects of everyday life. People engage with digital library
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analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for future autonomous instrument control and self-directed experimentation will be developed, recognizing
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novel opportunity to automate and improve the frailty assessment process, aiming for greater consistency and predictive accuracy. Aims i) Develop a deep learning algorithm to autonomously detect and
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industries which are the industrial driving forces for Australia. The invented technologies will help autonomous underwater vehicles to look for submerged resources, and aid resource exploration and extraction
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. Project goals The objectives of this project are: Study the data-based rapid identification method of landing landmarks to realize the intelligent environment perception of UAV's autonomous landing. A data