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seismic data to produce 3D geophysical models that will constrain the subsurface extent of rock units that might be suitable for hydrogen generation via radiolysis and/or serpentinization and identify
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applied physics other related disciplines. Demonstrated knowledge in at least one of the following areas: porous media flow computational fluid dynamics (CFD) pore-network modelling lattice Boltzmann method
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• Strong quantitative and programming skills; experience with seismic data analysis or numerical modelling is highly desirable• Excellent written and verbal communication skills• Ability to work
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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-style interventions, and preventative medication. Analysis will utilise best practice in health inequalities measurement, modern econometric techniques, behavioural experiments, and modelling
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with digital twin modelling, remote sensing, and cloud computing is valued, as is a commitment to learning and advancing in these areas. The successful candidate will have the ability to work with large
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are recruiting four PhD students for the following Projects: Project 1: Unifying on-farm data and crop models to enhance tactical crop decisions Summary: Despite the increasing availability of on-farm data and
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burden. This PhD project will be part of or augment a larger NHMRC Investigator Grant project ('Better feet, better lives') that aims to develop better predictive models that help identify people with
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, teams are adapting to significant technological advances accompanied by great volumes of incoming data. Such changes have the potential to improve capabilities in complex and uncertain conditions, but
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care. There is evidence that clinical debriefing models can mitigate the psychological effects of these stressful events and improve the psychological safety of their working environment to improve