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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 17 hours ago
, with relevance to submarine glacier melting and other ice-ocean interactions. The position will emphasize both numerical approaches (e.g., Large Eddy Simulation, Direct Numerical Simulation, multi-scale
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the supervision of Dr. Joseph Kwon. We’re seeking a creative Postdoctoral Scholar to join our team and advance cutting-edge multiscale and hybrid modeling—integrating first-principles simulations with
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mesoscale fractal geometry, creating physics-informed neural network models to analyze turbulent structures, and comparing simulation results to astronomical observations to develop methods for inferring
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in AI-modeling, Monte Carlo simulation, and coding. The successful candidate will work alongside a multidisciplinary team, leveraging artificial intelligence and computational methodologies to optimize
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for construction operations. The successful candidate will contribute to cutting-edge research in mixed reality (MR)-based simulation platforms, machine learning-based process optimization, and human-machine
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-on experience in training large neural networks (generative models). Hands-on experience in medical image reconstruction. Preferred Qualifications: Proficiency in Python, C/C++, and Unix-like operating systems
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: Using biogeochemical evolutionary models to simulate lifeless and inhabited worlds, and Developing disequilibrium-, redox-, and information-based metrics to understand and quantify the influence of life
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to join our interdisciplinary research group. The successful candidate will conduct original research in biophysical modeling and live-cell fluorescence microscopy, focusing on the actin cytoskeleton’s role
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-based experiments. Proficiency with scientific programming languages and analysis tools such as C++, Python, Geant4, and ROOT. Experience with simulation and modeling of detector systems and physics
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-on experience in training large neural networks (generative models). Hands-on experience in medical image reconstruction. Preferred Qualifications: Proficiency in Python, C/C++, and Unix-like operating systems