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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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an opportunity for a Postdoctoral Fellow. You will contribute to UNSW’s research efforts in developing machine learning algorithm for photovoltaic applications and utilising them for the investigation
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: Research: Development and validation of predictive maintenance algorithms for solar farms. Interface with industry partners for knowledge sharing and feedback. Play a key role in reporting to the funding
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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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Australian National University | Canberra, Australian Capital Territory | Australia | about 1 month ago
postdoctoral researcher with: A PhD (or near completion) in Computer Science, Computational Biology, Mathematics, Bioinformatics, or a related discipline. Proven expertise in machine learning and algorithm
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Australian National University | Canberra, Australian Capital Territory | Australia | about 1 month ago
Classification: Academic Level B Salary package: $118,632 - $134,507 per annum plus 17% superannuation Terms: Full time, Fixed term (up to 3 years) The Position This postdoc will explore
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algorithms and methods for adaptive and personalised feedback, modelling learning behaviours with sequence and deep learning methods, and generating interpretable insights through novel analytics and
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 2 months ago
&PEWER_Academic B_Research Fellow.pdf The Position This postdoc will explore the geochemical behaviour of critical metals in the Earth’s crust as a function of variables such as composition, temperature, pressure
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experience. Experience in analysing large, complex ecological or biodiversity datasets. Strong proficiency in statistical modelling, including experience with species distribution models, community ecology
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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