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dataset generation technique to optimize the training of neural networks (NNs) for seismic data prediction. The use of neural networks to predict seismic velocity models has shown increasingly accurate and
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of the North American Ice Sheet Complex forebulge. The candidate will calculate misfit values between the statistically modeled RSL and glacial isostatic adjustment (GIA) model predictions of RSL to identify
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learning models represent information internally and how their predictions can be made transparent, reliable, and clinically meaningful. This work will involve developing and applying interpretability
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computational datasets of disordered materials based on density functional theory calculations and training machine learning models to accelerate the predictions. This work will involve collaboration with Assoc
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technology. Development of cutting edge foundation models for protein design, small molecule property prediction, or protein function prediction Data generation and curation, including molecular simulation and
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, and protein structure prediction by artificial intelligence algorithms. The goal is to generate functional models of multimeric protein complexes and how they assemble as a guide to understand disease
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. The candidate will calculate misfit values between the statistically modeled RSL and glacial isostatic adjustment (GIA) model predictions of RSL to identify modifications to the ice history and Earth parameters
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 5 hours ago
focused on the classification and characterization of human and animal models tumors through the study of gene expression patterns, tumor DNA copy number changes, and DNA somatic mutations identified using
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their evolution over cosmological timescales, to the prediction of observable signatures today. These predictions will be tested primarily through gamma-ray, radio, and gravitational-wave observations. The two
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research will involve synergetic collaborations with a multi-disciplinary team involving engine modelers, CFD experts, and computational scientists to enhance the predictive capability for next-generation