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Field
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optimizing PIC algorithms for modern heterogeneous architectures, including CPUs, GPUs, and other accelerators, the project seeks to achieve unprecedented efficiency and resolution in plasma simulations
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conditions. Implementing a multimodal approach for large-scale data analysis using CPU and GPU Solutions at the UM6P Data Center. Innovate and improve image analysis algorithms for plant trait quantification
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performing routine maintenance on lab computing resources (e.g., Linux servers, GPUs, networked workstations). (10%) Performs other tasks, duties, and responsibilities as required Minimum Qualifications
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library research and field explorations. Run experiments, analyze results, and prepare research outputs. Execute large-scale training jobs on GPU clusters, track metrics, visualize findings, and contribute
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models, (d) experience in using high performance computing systems with multiple nodes and GPUs and (e) drought metrics. Familiarity with Texas water resources and management practices. Experience working
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of this role is to oversee the construction and management of a High-Performance Computing (HPC) cluster comprising 4,500 CPU/GPU cores, BeeGFS storage, and Infiniband interconnects. The ideal candidate will
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environments, cloud computing, or GPU-accelerated machine learning Background in Monte Carlo Tree Search (MCTS) or reinforcement learning for sequence generation Familiarity with biological sequence alignment
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libraries for modern architectures (e.g., GPUs). Exploration of linear algebra methods in computational physics applications and machine learning. Integrate and benchmark the GINGKO library, a sparse solver
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managing experiments using GPUs Ability to visualize experimental results and learning curves Effective inter-personal and team-building skills Self-motivated with an ability to work independently and in a
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, TensorFlow) with several years of practice Experience in maintaining high-quality code on Github Experience in running and managing experiments using GPUs Ability to visualize experimental results and learning