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models, recurrent neural networks, natural language processing, and ML ensembles in healthcare (or using health datasets) Demonstrated experience in developing/deploying machine learning models or AI
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executive functions, including decision-making, attention and predictive coding. Key responsibilities will include: Research: Undertake human testing, conduct analyses of behavioural and brain imaging data
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, and modelling to identify pathogens, beneficial microbes, and predict disease outcomes. Develop innovative, sustainable strategies for disease management and soil health diagnostics. Collaborate with
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: Developing and deploying machine learning models (e.g. graph neural networks, neural force fields, diffusion models) for molecular property prediction and molecular generation. Integrating quantum chemistry
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: Research: Development and validation of predictive maintenance algorithms for solar farms. Interface with industry partners for knowledge sharing and feedback. Play a key role in reporting to the funding
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have: A PhD in Statistics and relevant work experience in developing risk prediction models for Alzheimer’s Disease and dementia through secondary analysis of biobanks and cohort studies. Evidence of
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measuring prediction error signals in the brain. You will support the compelling hypothesis: a key function of sleep is to balance prediction and surprise. Key responsibilities will include: Research: Produce
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. Working closely with the ABI program’s leadership team, you’ll contribute to data curation, protocol development, predictive modelling, and novel analytics for large-scale neurocritical care datasets. As
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economies and prediction markets. Opportunity to supervise research students and work as part of a larger team. Opportunities for inter-disciplinary collaborations, and collaborate with industry and
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using structure prediction and/or machine learning methods is desirable. Please Note: Appointment to this position is subject to passing a Working with Children and National Police Check. About the RMIT