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-tracking, pupillometry), cognitive modelling, and regulatory analysis to assess how algorithmic explanations shape human judgement and how existing legal and ethical frameworks align with the evolution
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of classical and hybrid classical-quantum algorithms for treating the correlations. This position offers exciting opportunities for collaboration within UQ, across the QDA network, and with external research
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This project aims to develop robust algorithms capable of identifying and analyzing fingertips extracted from both static images and video footage. Machine learning techniques, particularly computer
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Status: Closed Applications open: 1/07/2024 Applications close: 18/08/2024 View printable version [.pdf] About this scholarship Description/Applicant information Project Overview Modern sensor data
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achieve recognition and impact in the research area, design PCBs and develops FPGA code, develop image signal processing systems and sensor motion control, collaborate on the assembly, alignment, and
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experiments for months before the value of output y is measured for some given input x. This creates an exciting challenge for AI researchers to develop smart algorithms that can find the optimal value of input
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-disciplinary research. With six research clusters spanning precision livestock management, horticultural innovation, sensor technologies, high-value cropping, agricultural education and extension, and
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modelling and simulation of transmission and distribution networks, including benchmarking data models, developing optimal power flow algorithms, and creating state estimation and multi-energy optimisation
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queries, and automating data transformations. By combining advancements in natural language understanding, algorithm synthesis, and debugging, the proposed framework will enable developers to efficiently
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duties will include: Undertaking installations and maintenance of proprietary hardware and software, sensors and cabling on mining equipment Working closely with clients, contractors and other staff