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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 7 hours ago
opportunities for career growth, skill development and lifelong learning and enjoy exclusive perks that include numerous retail and restaurant discounts, savings on local child care centers and special rates
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plasma. The main methods used are computer simulations for studying dust dynamics and analysing in situ measurements by spacecraft that carry a dust detector on board. We collaborate with researchers in
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competitive residency program with 25 positions, we offer 9 fellowships and participate in numerous graduate school and the MD/PhD program of the CU School of Medicine. Why work for the University? We have
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, engineering, materials science, maths, or computer science), or equivalent experience Experience with uncertainty quantification or error analysis Familiarity with numerical methods (e.g., Monte Carlo, Finite
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Knowledge of Matlab, and web-based technologies is of advantage Knowledge in using high-performance compute architectures Experience in implementing and optimizing scientific numeric analysis methods and
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professional values. In addition to a vibrant and highly competitive residency program with 25 positions, we offer 10 fellowships and participate in numerous graduate schools and the MD/PhD program of the CU
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system transient simulation concepts. Advanced mathematical knowledge in linear algebra and calculus. Expertise in numerical methods for solving large-scale power system equations. Programming proficiency
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; David Plant ECSE 335: Microelectronics; Gordon Roberts ECSE 343: Numerical Methods in Eng; Roni Khazaka ECSE 353: Electromagnetic Fields & Waves; Thomas Szkopek ECSE 354: Electromagnetic Wave Propagation
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learning Demonstrated expertise in software and algorithm development, computational methods, data analysis, modeling, machine learning, high-performance and parallel computing, or scientific simulation
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, which performs numerical analytics during the simulation. This is necessary due to the ever-growing gap between file system bandwidth and compute capacities. To this end, we are developing the Deisa