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Field
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progression. The models are informed by a variety of experimental data, utilize different model structures/modeling techniques, are often closed source or coded in proprietary software packages with poor
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doctoral degree (or equivalent) and is engaged in a temporary and defined period of mentored advanced research training to enhance the professional skills and research independence needed to pursue his
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ecological systems. • Knowledge of urban ecosystems and urban ecology is preferred. • Experience with R, Python, or other programming languages, as well as QGIS/ESRI spatial software. • Experience working with
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: Experience in the following will be preferred: The development of computational models to represent structural performance using commercial and research software tools The development and validation of machine
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methods and software for the analysis and calibration using very large data sets resulting from dynamical simulations on high-performance computing resources. Application areas include : 1. Epidemiology, 2
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of improving human health. Aligned with Rutgers University–New Brunswick and collaborating university wide, RBHS includes eight schools, a behavioral health network, and five centers and institutes that focus
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-related experiments in EPPL. Assist in the preparation of research publications and technical reports. Contribute to the development of software and hardware systems for real-time control applications
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evaluate distribution networks in OpenDSS; investigate feeder- and system-level impacts of DERs (e.g., load flow, hosting capacity, voltage regulation). Develop and refine T&D co-simulation platforms (e.g
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)—topics including, but not limited to: · Physics-informed neural networks (PINN) & neural operators · Physics-aware convolutional neural networks (PARC) · Meta-learning/transfer
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, human-systems interactions, networks science, information, decision complex networks, dynamic data-driven application systems, the science of information computation and fusion, systems and software