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algorithms for computing MML solutions beyond the one-dimensional case. Extend existing dynamic programming approaches to higher-dimensional problems or develop novel approximation methods that preserve
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strong sense of community & inclusion Enjoy a career that makes a difference by collaborating & learning from the best At UNSW, we pride ourselves on being a workplace where the best people come to do
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algorithms and techniques and design, implement, test, and maintain software/tools embodying those methods. You will prepare and submit grant proposals to external funding bodies. This position will also
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of the postdoctoral researcher will include: To work closely and proactively with Prof Anton van den Hengel to scope and develop research ideas. To develop algorithms, machine learning models, Python modules
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ideas. To develop algorithms, machine learning models, Python modules, demonstrators and training pipelines for publication and translation into commercial products that can be widely and reliably adopted
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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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extraordinary ideas - and the people who discover them The Opportunity We are seeking a highly motivated Research Fellow to join the Faculty of Science and School of Physics and Astronomy to develop methods
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explore unconventional ideas, develop computer algorithms for data analysis, create new experimental approaches, and apply the technique in areas like biomedicine, materials science, and geology. My group
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This project focuses on developing algorithms capable of automatically identifying and categorizing mobile ringtones. This involves leveraging machine learning techniques to analyze audio signals
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formula is true or false (EXPTIME vs NP). Can we develop and implement efficient algorithms for this problem? This problem has been attacked using multiple different methods for the past 40 years, without