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Field
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particle physics, computer science or a related field Experience with large-scale data management using grid or cloud technologies Experience in one of the on-site experiment would be an asset Familiarity
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machine learning techniques, will quantify groundwater recharge and groundwater resilience. Your responsibilities: Analyse the dynamics of hydrological connectivity of soil moisture using gridded soil
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aims to simulate time-evolving supernova-CSM interaction with varying physical parameters, and construct grids of photometry, spectroscopy, and polarimetry based on the radiative output, to be compared
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of hydrological connectivity of soil moisture using gridded soil moisture data sets and data-driven approaches (e.g., complex network methods) Develop models to predict gatekeeper locations and their relationship
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of new positivity-preserving entropy stable spectral collocation schemes for simulation of 3-D compressible viscous flows on unstructured grids. Our department has a history of producing exceptionally
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prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a sustainable future. These EMS coordinate
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algorithms, and prototypical systems controlling complex energy systems like buildings, electricity distribution grids and thermal systems for a sustainable future. These systems coordinate distributed
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
grid model applications to assess individual source sector contributions, and b) develop quantitative estimates for air quality and health risk assessments. The candidates will work on a range of tasks
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from China, Iran, and Russia Preferred Qualifications Experience with modeling high power systems such as advanced inverters (grid-forming techniques), generators, flywheels, motors, Electric vehicles