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. Individual will develop and test novel computational models of the neural activity generated by electrical stimulation of the brain. Also, perform data analysis utilizing medical imaging data, computer models
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on identifying and understanding evolutionary changes in developmental gene regulatory networks of sea urchins. Projects focus on the genetic and molecular basis for changes embryonic patterning and cell fate
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quality monitoring, drone surveys, digital twins and ecosystem service modelling to generate estimates of ecosystem functions and services provided by a living shoreline that is being constructed at Marine
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new NIH-funded Center for Excellence in Multiscale Immune Systems Modeling. This position focuses on leveraging and developing new equation learning methods, such as Physics-Informed Neural Networks
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, and (b) the critical role of structural and functional connectivity using combined tractography and graph theory analyses. Our modeling of mnemonic representations uses the latest tools available to AI
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, evolutionary biology, computer science, physics, applied mathematics, or engineering. Our research integrates mathematical modeling, machine learning, and quantitative experiments to understand and control
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Systems Modeling. This position focuses on leveraging and developing new equation learning methods, such as Physics-Informed Neural Networks (PINNs), Biologically Informed Neural Networks (BINNs), and
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research topics include mathematical modeling of microtubule dynamics in neuronal cells, analysis and simulation of RNA transport and organization in developing cells, and parameter inference and
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cultured cells and animal models of skin diseases. Work Performed • Development of new and implementation and modification of existing experimental procedures. • Data preparation for oral presentations
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will lead methodological innovation and applied research in predictive modeling for mental health, drawing on diverse data modalities such as: Electronic Health Records (EHR) Patient-reported outcomes