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Field
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and localization of a potential fault using the Matched Field Processing (MFP) method, based on the reconstruction of a response model of the inspected structure from the modal parameters predicted by
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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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applications. A reverse modeling strategy will be used to design an optimum test matrix. This framework will enable modeling and predicting ion-irradiated mechanical properties using reduced test data, thereby
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, and publication of major results from the experiment. They will also lead the development of predictive distribution models that incorporate data from the experiment. The project is funded by the USGS C
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, predictive models of neurodegenerative disease with a focus on Alzheimer's Disease. Computational models will be developed that utilize data obtained from a wide range of experiments, from basic biochemical
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, integrating novel genetically related traits using digital tools or functional genomic information or OMICS to improve genomic prediction models. The successful candidates will have the opportunity
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/or high-temperature heat pumps based on power cycles. Design thermal and/or thermochemical energy storage systems. Implementing and validating advanced thermodynamic models for performance prediction
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promoters. You will train and evaluate predictive models in model/crop species with different levels of genome complexity. You will work very closely together with your dry-lab colleagues for data processing
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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level of detail extracted from these experiments. As part of this role, you will work closely with other researchers to translate these experimental results into our numerical models, helping to improve