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inference) Algorithmic development for bilevel (or multilevel) optimization Methodological developments in Bayesian statistics and/or decision analysis Application of adversarial risk analysis within security
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data processing Understanding of generating computer algorithms for disease trends is desired. Informatics experience, including software applications for public health analysis. Background in
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environments, scripting languages for handling large-scale genomic data, and learning how to apply programming languages to implement complex computational models and algorithms. Learning objectives will include
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Linux environments, scripting languages for handling large-scale genomic data, and learning how to apply programming languages to implement complex computational models and algorithms. Learning objectives
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-Informed Neural Networks (PINNs) and hybrid models that respect the physical laws governing the real-world system Applying Deep Reinforcement Learning (DRL) algorithms to optimize processes within simulation
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developing algorithms for RNA-seq and whole-genome data. Learning Objectives: Under the guidance of mentors, you will have the opportunity to learn to: (a) conduct research using swine infection models; and (b
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precipitation observation on the global scale. The Mesoscale Atmospheric Processes Laboratory at Goddard Space Flight Center leads research aimed at algorithm improvements to create state-of-the-art global
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biological and biogeochemical constituent concentrations and rates from the derived optical properties. Specifically, the aims are to develop advanced algorithms to retrieve from PACE and GLIMR remote sensing
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the development of image/signal processing algorithms from a multidisciplinary approach, to include multiple sensor modalities. These multidisciplinary research opportunities incorporate theoretical and
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control systems and thermal protection for on-board actuation systems. The candidate will have a deep knowledge of smart material based actuators, mechanisms, advanced control algorithms, and thermal