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involve the development of novel lattice QCD algorithms and high-performance computing (HPC) codes, and/or exploring applications of artificial intelligence (AI) to lattice simulations. The starting date is
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computing (HPC) development of SeA (in collaboration with the DiStasio research group at Cornell University) and the broader QE package. We also expect this position to offer many other collaborative
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are comfortable navigating complex HPC environments and wrangling large datasets. You have experience with modelling through state-of-the-art machine and deep-learning methods and with hands
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geologic media As for programming, we prefer familiarity with MATLAB, Python, and C++. Prior experience with high-performance computing (HPC) clusters and Unix operating systems is advantageous. We welcome
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for your research group(s) and improve the use of computing among all group members. Stay up to date with the latest HPC, AI, and general computing/data management practices, evaluate latest developments
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-house CFD software packages. (3) Designing and developing CFD sub-models for application to a broad range of CFD problems. (4) Using high-performance computing (HPC) to accelerate complex, large-scale
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spatial distribution of critical topsoil properties in global drylands. Process large-scale geospatial and remote sensing datasets using High Performance Computing (HPC) systems. Conduct data analysis, and
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, Astronomy, or a closely related field is required. Experience with HPC systems, machine learning, and GRB monitor data analysis would be an advantage. Additional Information Applications must be submitted
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wind tunnels such a temperature/pressure sensitive paints, infrared thermography, PLIF, FLDI etc. • Proficiency in Python • Experience running simulations with high performance computing (HPC) resources
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consulting and data management services to UM6P researchers and their collaborators. UM6P has state of the art NGS sequencers and mass spectrometry and the largest HPC (High Performance Computing) cluster in