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applications would be particularly beneficial, although not essential. In addition, experience in artificial intelligence, cloud computing, sensor networks and/or data visualisation would also be highly
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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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the electronic structure of these materials. This position offers exciting opportunities for collaboration within UQ, across the QDA network, and with external research partners. Key responsibilities will include
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data analysis (TDA) techniques such as persistent homology, with application in real data sets such as biomolecular data and network data Perform data preprocessing, feature extraction, and analysis
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network of academic and industry experts shaping the future of smart shipping and maritime decarbonisation. As a university, we are committed to creating an inclusive environment that fosters respect
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and beyond, and participating in research networks such as the Collections-Connections-Communities initiative. We particularly encourage applicants who will seek to bring new perspectives
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to empower recent Ph.D. graduates to conduct world-class research, publish in top-tier journals, and build a robust scientific network. By joining us, you will receive the mentorship and support necessary
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sources. Proven track record leading collaborative industry-academia research projects in carbon management in the mining industry, including carbon accounting, net zero target setting, and carbon offset
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in the area of distributed radar we are looking for a research fellow with expertise and experience in this area. Experience with highly accurate time synchronization of data received by a net of radar
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of supportive initiatives, including leadership training, mentorship for early career progression and promotion, networking opportunities, and other professional development resources. As reflected in