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National Aeronautics and Space Administration (NASA) | New York City, New York | United States | 3 days ago
system. Climate models are important tools for improving our understanding and prediction of atmosphere, ocean, and climate behavior. We seek candidates with an interest in advancement of radiative
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- specific predictive models, the lack of explainability in AI-driven decision processes, and the difficulty of capturing long-term dependencies in time-series data. In this project, you will focus
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, as well as from industry. The successful candidate will work in the established collaboration between DSB and ICGI to develop multimodal deep learning models for predicting prostate cancer
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attention to scientific rigor and interpretability Experience with XAI tools (SHAP, LIME, Integrated Gradients) to identify which features of the model are driving the predictions Clear written and verbal
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, product management work, and and leadership responsibilities • Familiarity with artificial intelligence and machine learning approaches, including predictive modeling and precision analytics applied
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Charité–Universitätsmedizin Berlin (Dr. Rosanna Sammons); for further information, see https://www.sfb1315.de/ - development of network models of the CA3 region of the hippocampus - investigation
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; machine learning methods (i.e. supervised and unsupervised learning, deep learning, reinforcement learning, etc.); artificial intelligence methods (e.g., predictive modeling, natural language processing
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modeling – including predictive models for Alzheimer’s disease with a particular focus on sex-specific (female) risk. The harmonization pipeline will integrate female-specific and cognitive variables/items
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quantification, in particular the theory and methods known as predictive Bayes. Predictive Bayes theory involves getting Bayesian type uncertainty for parameters given data (i.e., a posterior type distribution
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have extensive knowledge on processes governing cross-shore transport and can use experimental data to develop predictive models. Experiences within numerical modelling of coastal processes is considered