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Field
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region surrounding Fayetteville is home to numerous Fortune 500 companies and one of the nation’s strongest economies. Northwest Arkansas is also quickly gaining a national reputation for its focus
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substantial deliverables. Ideal candidates will also have expertise in renewable energy, energy in buildings, the impact of occupants on energy use and data acquisition and analysis. Energy modelling expertise
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cell biology, molecular biology, immunology, CRISPR-Cas9 technology and working with pre-clinical cancer models. You will have a proven track record of research achievement and the ability to articulate
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material design process. Some potential key research objectives: AI Model Development: Create machine learning models to predict FGM properties based on compositional gradients and processing conditions
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implement a framework to infer anisotropic viscosity from both ice and mantle textures in a numerical flow model. This will open new avenues for understanding solid earth and cryosphere dynamics, and their
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balance modeling techniques (see below) with existing datasets of field-observed microclimate measurements (e.g. temperature and soil moisture) under various vegetation structural conditions. Objective 2
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) and economics (or related fields). Applicants must have experience in one or more of the topics: Model-predictive control Numerical optimization Econometrics Virtual power plants Power systems and/or
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quantum phenomena in strongly correlated systems; Analytic or numerical methods of quantum many-body systems and non-equilibrium systems; Quantum field theory; Modeling and calculation of solid-state
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help to realize them experimentally on our quantum simulator. We are especially interested in simulating quantum many-body models relevant to materials science and condensed matter physics. We are also
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estimated stepwise from time series of the RS images, numerical models can provide continuous predictions of drift and deformation fields. This project shall investigate how the combined use of image time