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activity, sleep and health behaviour change Project Description: Digital behaviour change tools reach large populations cheaply, but most deliver generic advice and lose their users within weeks. Large
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datasets with different configurations (e.g., number of channels, sampling frequency and resolution). To leverage large-scale self-supervised learning to train models on unlabeled EEG data, reducing reliance
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social media and online platforms. The project will use natural language processing (NLP), large language models (LLMs), and network analysis to identify coordinated harassment, anti-gender equality
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I specialise in the numerical modelling of high-energy particle collisions , such as those occurring at the Large Hadron Collider. Accordingly, most projects I offer straddle the intersection
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investigate the scientific, technical and institutional innovations required to enable large-scale impact. Successful candidates will join the Transforming Cities Hub at Monash University and work within an
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to work with large volumes of data and produce accurate reports. The successful candidate will learn quickly, adapt to changing priorities, and take ownership of projects, while working effectively with
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infrastructure, public safety and smart environments. The successful candidate will be supervised by Dr Deval Mehta within the Department of Data Science & AI, Faculty of Information Technology, Monash University
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is carried out within the LHCb collaboration that runs one of the four large experiments at the Large Hadron Collider at CERN as well as towards future collider developments. I supervise a number of
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someone with strong quantitative skills and an interest in using data to answer policy relevant research questions. The successful applicant will work with large administrative and survey datasets and apply
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” of novel stretchable structures by advancing numerical modelling, data-driven, and optimisation approaches in a nonlinear regime. Project Background Stretchable mechanical structures are a subset of