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PhD Scholarship in Big Data and Analytics for Crop Genetics Modern agriculture and biomedical research are driven by the availability of big data and the development of data science. The recent
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, candidates could choose to align with, expand upon, or pivot from existing initiatives such as: Example 1: Big Data & Infection Risk Prediction (Stream: Infection Prevention) The Scope: Leverage large, linked
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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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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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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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and complexity of Australia’s work disability support systems negatively impacts the health and employment of a large number of citizens seeking support through these systems. Other high-income
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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