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observations and population synthesis to explore evolutionary pathways and physical mechanisms underpinning these enigmatic sources. Key Responsibilities Analyse archival MWA and ASKAP datasets to detect and
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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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an opportunity for a Postdoctoral Fellow. You will contribute to UNSW’s research efforts in developing machine learning and deep learning algorithms for dynamic systems (sequential or time-series data). Experience
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to research-based activities, including the development of new data analysis algorithms, processing and analysis of field data, and participation in the fieldwork. Your responsibilities will include: Conduct
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programming and data analysis. Interest in developing methods, algorithms or software. Evidence of publications in high-quality peer-reviewed journals. Excellent communication skills. Experience
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. The tasks of the postdoctoral researcher (innovation) will include: Conduct world-class research in foundational AI, with a focus on applications in the financial sector. Develop innovative algorithms
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research on designing mobile energy hubs, energy systems integration, resilience analysis, and developing digital twin models and AI-enabled algorithms. You will conduct lab and field tests, analyse data
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quantum engineering, quantum computing, and/or quantum information sciences A deep understanding of quantum algorithms and/or experience with quantum hardware will also be beneficial. A passion for
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on clusters and high-performance computing infrastructure), Information Retrieval methods, Machine Learning algorithms, wrangling large-scale datasets, and showcasing the research results. The ability to work