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of Power Engineering; Xiaozhe Wang ECSE 408: Communication Systems; Ioannis Psaromiligkos ECSE 412: Discrete Time Signal Processing (cross-listed with ECSE 512); Benoit Champagne ECSE 420: Parallel Computing
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of their respective concentrations will be investigated and correlated with the velocity field recorded by PIV (Particle Image Velocimetry). In parallel with the use of standard post-processing methods, an innovative
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associate in the broad areas of high performance computing and machine learning. HighZ is focused on developing scalable high order methods, enhanced with surrogate models for subscale physics, for modeling
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machine learning methods for computational materials physics and chemistry. Projects include: The aim is to develop generalized equivariant neural network models NequIP and Allegro for machine learned
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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. Our faculty and staff are diverse and gender balanced
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, numerical methods, or Geant4 / Monte Carlo simulations. Proven experience in scientific software development using C/C++, Python, MATLAB, CUDA, and/or other relevant programming tools. Demonstrated ability
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working on related topics Participate in teaching and supervision activities, in line with the candidate's profile and interests The research activities will be hosted by the Parallel Computing and
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simulation environments and real-world deployments with the nano-drones of the University's SwarmLab The research activities will be hosted by the Parallel Computing and Optimisation Group (PCOG) at SnT
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, you’ll join a technically driven, publication active team known for research in computational modelling, CFD, numerical methods and high-performance computing, with a strong culture of code quality, open
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