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Field
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Programming Interfaces), high-performance computing cluster, Bash or GPU programming is preferred. When submitting your application, please list your programming experience, including your depth of knowledge
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,maintains, and supports imaging analysis environment, including a GPU-equipped workstation for quantitative CT (qCT) analyses such as lung segmentation, and installs, configures, and manages related analysis
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engineering or digital twins. - Experience with scientific visualization tools and methods. - Experience with NVIDIA CUDA or GPU computing. - Experience with Docker or Kubernetes containerization and
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simulation, Cosserat rod theory to support hands-on class activities and development of NVIDIA GPU-based course modules. • Availability to schedule, coordinate, and oversee student visits to operating rooms
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Center for Generative AI hosts the largest academic GPU cluster in the world and includes one of our faculty members on its team. The Texas Advanced Computing Center provides world-class AI compute
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). Practical experience with cloud computing platforms (e.g., AWS, GCP, Azure). Additional Qualifications Experience with multi-GPU model training and large-scale inference. Familiarity with modern AI
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team and supported by cutting-edge HPC and GPU infrastructure, you will contribute to internationally leading research, publish in high-impact journals and present your work at major scientific
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large GPU clusters on cryoSTEM datasets in the multi-terabyte range. This position plays a pivotal role in supporting ongoing, high-impact research programs within our lab. The successful candidate will
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Nextflow or Snakemake, version control such as Git, and reproducible computational environments is preferred. Familiarity with GPU-accelerated genomics, high-performance computing, or cloud-based analysis
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foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across large GPU clusters on cryoSTEM