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Field
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project focuses on environmental sustainability in grain storage, developing telemetric robotic sensing and predictive modelling to control mycotoxin (Ochratoxin A) risk while reducing postharvest drying
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If you want to pursue a research career at the intersection of additive manufacturing (AM), microstructural engineering and advanced statistical/machine-learning (ML) based modelling, then this PhD
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at the tumour margin represent a key target for earlier and more effective therapeutic intervention. This PhD project will develop advanced MRI analysis methods and imaging-driven predictive models focusing
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regimes. This PhD project aims to develop predictive pore network models integrated with thermodynamics and upscaling methods toward reservoir-scale applications. We seek candidates with a strong background
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to correct or account for these biases, and build predictive models that simulate biological responses to in silico perturbations such as genetic or pharmacological interventions. The project aims to advance
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the service life of infrastructure. The research content includes: real-time data analysis and modeling pipeline network dynamic prediction and state identification optimisation algorithm and high-performance
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Water consumption under various application parameters Impact of dosing changes on crop quality Economic efficiency Impact on variability of soil properties Predictions based on AI models Supervisor
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primary supervision of Dr Thomas Ouldridge. The student will develop predictive models of nucleic acid strand displacement rates to allow the rational design of complex networks of ever-increasing
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target for earlier and more effective therapeutic intervention. This PhD project will develop advanced MRI analysis methods and imaging-driven predictive models focusing on the glioblastoma infiltrative
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Asia (SEA), focusing on Manila (Philippines) and Ho Chi Minh City (Vietnam). This position will be based at the School of Engineering at Newcastle University, focusing on developing models to predict AMR