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modeling, machine learning, or data-driven prediction methods applied to environmental datasets. Experience building and maintaining large, frequently updated archives of weather or climate observations
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large dataset of P. aeruginosa genomes and experimental metadata to predict key mutations to the organism. The postdoctoral researcher will join the Whelan lab led by Dr. Fiona Whelan. The Whelan lab is a
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, regulatory, or multimodal biological data. Support target and mechanism prioritization by integrating model predictions with biological knowledge and external data sources. Work closely with academic partner
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tools, such as physics-informed climate and weather predictive models, and trustworthy datasets for training and analysis. Its work aims to improve prediction capabilities and understanding of climate
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FLAME-GPU accelerated agent-based modelling of material response to environmental and operational loading EPSRC CDT in Developing National Capability for Materials 4.0, with the Henry Royce
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, regulatory, or multimodal biological data. Support target and mechanism prioritization by integrating model predictions with biological knowledge and external data sources. Work closely with academic partner
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underwater acoustics and marine ecology. CMST pioneers innovative methods to monitor and manage marine environments. We measure, monitor, model, and predict anthropogenic noise. We are experts in sound
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management and finite element modelling. Applicants who are in their final year of the first degree study are also encouraged to apply and will be initially employed as RSA. The University of Malta is an
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predictive analytics. Identifies and investigates significant differences or anomalies in data. Uses appropriate quantitative and qualitative analysis to analyze survey data. Conducts longitudinal analysis and
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, assess the health state of systems, and predict their future evolution and remaining useful life. The proposed approach integrates physics-based and data-driven modeling techniques, including machine