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conducting lifetime modeling, developing advanced condition monitoring techniques, and applying data-driven analytics for lifetime prediction. You will play a central role in integrating experimental insights
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conditions and associated microbial mechanisms. A postdoctoral researcher will participate in the analytical protocols, acquiring multidisciplinary skills and enhancing their visibility within the geobiology
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uses a range of approaches, including in vivo and ex vivo mouse models, primary human cell culture, and in vitro organoid cultures. Responsibilities Responsibilities include conceptualizing and
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preferred. Prior work experience in public health, epidemiology, and/or biomedical research is desirable. Experience in mixed models, and experience with longitudinal data analysis, functional data analysis
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road conditions. Your specific activities will include (but are not limited to): • Develop robust, production-grade machine learning solutions for predictive modelling and complex decision
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applications of data science and modelling. The successful candidate will support the research of Professor Lucy Marshall, Faculty of Engineering and will collaborate with members of her cross-institutional
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engineer and Postdoc P1 to ensure cross-vector coherence in infrastructure models and boundary conditions. Participating in the design and execution of scenario simulations, including policy- and technology
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and dynamic wave propagation, in particular: (i) developing domain decomposition methods, (ii) damage models, (iii) nonlinear mechanics. 2) Validate the model by performing simulations using
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, and function across the lifespan – including in neurotypical populations and those with neurodevelopmental, mental health, and psychiatric conditions. Specifically, the candidates will have expedited
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for working with both public health and/or environmental data/models, and experience working with an interdisciplinary team of researchers and stakeholders. This position is based at the Kansas Geological