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Nuffield Department of Clinical Neurosciences (NDCN), MRC Brain Network Dynamics Unit, Mansfield Road, Oxford The post holder will develop computational models of learning processes in cortical
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Postdoctoral Research Associate in Global Environment Modelling of Soil Organic and Inorganic Carbon
- $121,054 + 17% superannuation About the opportunity The School of Civil Engineering at The University of Sydney is recruiting for a Postdoctoral Research Associate in Global Environment Modelling of Soil
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des Fluides et d'Acoustique - LMFA) develops a continuum of research in fluid mechanics and acoustics, from the understanding and the modelling of physical phenomena to applied research, in
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medication use Applying frameworks such as the Andersen Behavioral Model (ABM) and 4Ms of Geriatrics Conducting advanced data analysis and predictive modeling Engaging patients, caregivers, and health system
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Vitro to In Vivo Extrapolation of Toxicant Effects on Ovarian Function” and will focus on phthalates and developing models that extrapolate in vitro assay results to predict in vivo effects on ovarian
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academic and industrial domains. The scientific outcomes are expected to be significant in: Earth system science – by improving models of Earth surface evolution and enabling better predictions of landscape
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, through developing predictive models and new experimental methods and instrumentation, to design creative and cost effective CO2 trapping processes. The need is urgent, the task is challenging and a
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methods to predict the origin and dispersal patterns of genomic sequences, with applications ranging from biogeographical mapping to paleogenetic reconstructions. The candidate will work jointly with Dr
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thermal and/or thermochemical energy storage systems. Implementing and validating advanced thermodynamic models for performance prediction and optimization. Collaborating with experimentalists and industry
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real-time vector-borne disease risk assessment in low resource areas. The postdoctoral fellow will be directly responsible for the development of adaptive predictive models for nowcasting vector-borne