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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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, 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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will play a pivotal role in advancing research in artificial intelligence (AI), energy-efficient computing, foundational mathematical models, high-performance computing (HPC), dimensionality reduction
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models (e.g., CNNs, diffusion models, etc) Proficiency in Python Experience with HPC (CPU or GPU, with GPUs preferred) Related Skills and Other Requirements Ability to collaborate on the application of AI
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, Python, Bash, and other programming languages for data analysis and statistical modeling. Automated Workflows Experience: Proficient in using HPC, Git/GitHub, Nextflow, Snakemake, or Docker for efficient
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/interest with or prior experience working with NGS algorithms such as PLINK, or experience working in a cloud computing environment or UNIX/linux/HPC cluster. Department Contact for Questions Dr. Bohdan
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. Familiarity working with publicly available genomics data and working in high-performance computing (HPC) and/or UNIX environments is a plus. Highly motivated, able to creatively take initiative to see your
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of scientists and High-Performance Computing (HPC) engineers. In the AL/ML group, we work at the forefront of HPC to push scientific boundaries, carrying out research and development in state
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, Matlab Preferred Qualifications: Experience in thermos-fluids in porous media. Experience in High-Performance Computing (HPC) on CPU or GPU platforms. Experience in mentoring of graduate and undergraduate