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. Expertise in the evaluation of novel predictive agriculture methods such as crop and cropping systems growth models to support decision making, i.e. economic control thresholds for abiotic stressors, input
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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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response to perturbations, and devising reliable automatic schemes for predicting this emergence and quantifying their response. About the role Level A - $113K - $121K plus 17% Superannuation and annual
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are being assembled to work together on tracking and predicting the future of the East Antarctic Ice Sheet. The successful candidate will bring their expertise in satellite altimetry and/or gravimetry
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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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: 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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, 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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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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: 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