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behaviour interventions, randomised control trials and longitudinal studies. As a registered psychologist, he has focused primarily on the behaviours of alcohol consumption, smoking, illicit drug use, mental
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to real ChIP-seq and CLIP-seq datasets with well-defined binding sites as a control that it works with real biological data Apply MML to ChIP-seq cardiac datasets where no primary or secondary binding site
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known as Team COMPAS -- includes a number of amazing undergraduate and graduate students, postdocs, alumni, and other fantastic collaborators. Please contact me if you are interested in joining our group
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theoretical colleagues. All research takes place within our dynamic particle physics research group with academics and postdocs, as well as graduate and undergraduate students. Some work will be purely
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information about behavioural patterns, but scoring this manually is time consuming. For this reason, machine learning solutions have been developed to automate behavioural prediction [5-12]. DeepLabCut [5] is
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Addiction Studies and holds an NHMRC Leadership Fellow in the School of Psychological Sciences, Monash University. His research focuses on the cognitive and neural mechanisms underpinning executive control
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Testing self-driving cars is extremely difficult, as one has to account for a very large space of possible scenarios. In this project, we will explore the application of automated testing techniques
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. Machine learning has been found to introduce and perpetuate discriminatory practices by unintentionally encoding existing human biases and introducing new ones. In this project, we will develop automated
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Research data governance is an under-explored issue, and technical infrastructures to support the transparency and control of data collected in human research studies (from medicine to social
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on this technology for its automated warehouses and fulfilment centres. The aim of this project is to use discrete optimisation techniques (e.g. Integer Programming) to design new algorithms for MAPF. An example