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. Ability to succeed in an interdisciplinary team and communicate results clearly in writing and presentations. Desired Qualifications: Knowledge of GPU architecture and GPU programming. Interest
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computing capabilities with an in-house cluster serving 80 CPU cores and 1.5TB of RAM, as well as a newly acquired NVIDIA DGX box with eight H100 GPUs and 224 CPU cores. We analyze large public datasets
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communicate results clearly in writing and presentations. Desired Qualifications: Knowledge of GPU architecture and GPU programming. Interest or experience in distributed training on large scientific datasets
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part of the core PLI team, which includes top-tier faculty, research fellows, scientists, software engineers, postdocs, and graduate students. Fellows will have access to the AI Lab GPU cluster (300
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for improved interpretability and generalization. Familiarity with high-performance computing (HPC), cloud platforms, or GPU clusters. Demonstrated ability to work collaboratively in interdisciplinary and cross
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and Machine Learning tools and algorithms to solve hydrology and water resources problems. Familiarity with high-performance computing (HPC), cloud platforms, or GPU clusters. Demonstrated ability
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algorithms to solve hydrology and water resources problems. Familiarity with high-performance computing (HPC), cloud platforms, or GPU clusters. Demonstrated ability to work collaboratively with
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molecules [doi.org/10.1021/jacs.2c07572 , doi.org/10.26434/chemrxiv-2023-5kl9x ]. (iii) Developing GPU-accelerated multireference methods to improve the accuracy and robustness of current state-of-the-art
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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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has also been developing physics-based machine learning algorithms for three dimensional seismic modeling, imaging and inversion using high performance computation including parallelization on GPUs