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radiation therapy. The primary aim of this research is to develop real-time target tracking and/or dynamic imaging algorithms for implementation within radiotherapy and medical imaging. Within our research
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frameworks (MOFs), and related materials using hybrid classical-quantum algorithms. A key component of the role involves using first-principles methods that capture strong electronic correlations, such as DFT
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disease patients using radiation therapy. The primary aim of this research is to develop real-time target tracking and/or dynamic imaging algorithms for implementation within radiotherapy and medical
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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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, and may utilise iterative algorithms, machine learning and high-performance computing. Through the Monash Centre for Electron Microscopy, opportunities exist to acquire large experimental datasets using
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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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out from our world class teaching hospital at the Flinders Medical Centre in South Australia to multiple rural clinical locations all the way to Darwin in the Northern Territory. Our research and