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structure prediction. Working at the intersection of generative AI and biophysics, the Fellow will focus on expanding the current framework to model dynamic protein ensembles. As an Empire AI-funded fellow
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· incorporating, as pedagogically appropriate, current technology in classroom, distance learning and laboratory environments · creating and modeling a quality learning environment that supports a diverse student
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Job Purpose To carry out research relevant to the research project HiPOVor: Modelling of high-power vortex induced turbulence in free-space and fluid dynamic based optical propagation modelling
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properties, scatterometer wind products are commonly estimated from empirically derived geophysical model functions (GMF). The scatterometer-derived ocean surface wind vector data have proved to be very useful
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the Center for Innovation in Brain Science (CIBS) and Department of Pharmacology at the University of Arizona is currently seeking a Postdoctoral Research Associate to work on research projects related
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to understanding future ice loss and global sea level rise. In this project we will perform a systematic assessment of the role of AEWE on firn evolution using the community firn model, and perform forward
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: how can physics-based flow modelling be coupled with advanced optical sensing to infer methane emission rates accurately and with quantified uncertainty? The project will pursue three core objectives
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multiphysics models to investigate aquifer-based compressed air energy storage (CAES) systems. The research will involve coupling fluid flow, heat transfer, geomechanics, and potentially reactive transport
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required. A background in immunology and/or vascular biology is preferred but not required. Experience with the phenotyping of animal models (cell isolation and organ processing) and immune (flow and/or mass
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models, high-dimensional flow cytometry, immunofluorescence imaging, and single-cell RNA sequencing to better understand immune cell dynamics in cancer. You will support a range of research projects within