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While deep learning has shown remarkable performance in medical imaging benchmarks, translating these results to real-world clinical deployment remains challenging. Models trained on data from one
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I supervise computational projects in electron microscopy imaging for investigating materials at atomic resolution. Some projects centre on analysing experimental data acquired by experimental
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) to support surgeons, operating room technicians, and other professionals in and around operating room activities. Particular areas that may be explored are: Immersive OR analytics: using XR to analyse data
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Methods of balancing model complexity with goodness of fit include Akaike's information criterion (AIC), Schwarz's Bayesian information criterion (BIC), minimum description length (MDL) and minimum
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Minimum Message Length (MML) is an elegant information-theoretic framework for statistical inference and model selection developed by Chris Wallace and colleagues. The fundamental insight of MML is
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The United Nations Development Programme has identified access to information as an essential element to support poverty eradication. People living in poverty are often unable to access information
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and communication skills in healthcare. You will use sensor-technology to capture multimodal ‘trace’ data including gestures, speech, workspace spatial layout and manual handling of objects. You will
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information that is encoded in the x-ray wavefield as it passes through the sample. My research aims to tap into the wavefield phase to reveal weakly-attenuating objects like the lungs that are almost invisible
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will have the opportunity to interact with gravitational-wave researchers throughout Australia and around the world. Students in my group use data from the Laser Interferometer Gravitational-wave
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Candidates should hold a previous degree (Bachelor’s and/or Master’s) in Computer Science, Data Science, Robotics, Mechatronics, or Software Engineering, with demonstrated knowledge in machine