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completed by the start of employment. Skills and Knowledge: Knowledge and understanding of water data; managing and analyzing large, multi-dimensional datasets; spatial and temporal statistics. Knowledgeable
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support on foundation models and generative AI systems; (b) explore advanced techniques in foundation large language models and multimodal large language models, with a focus on pre-training, post
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successes, ARL civilian employees helped develop the proximity fuze, worked to develop ENIAC (Electronic Numerical Integrator and Computer, the first operational, general purpose, electronic digital computer
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: The SCINet/Big Data Research Participation Program of the USDA ARS offers research opportunities to motivated postdoctoral fellows interested in solving agriculture-related problems at a range of spatial and
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aspects of ICT (Information and Communication Technologies). It is home to over 200 researchers with expertise in all communication and broadcasting systems and has developed the best-in-class large scale
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focus on translational Research, Development & Deployment which focus on specific area of the energy value chain, and a number of Living labs and Testbeds which facilitate large scale technology
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aspects of ICT (Information and Communication Technologies). It is home to over 200 researchers with expertise in all communication and broadcasting systems and has developed the best-in-class large scale
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analysis. · Advanced programming and workflow development skills in Python, R, Bash, and related computational tools for large-scale data analysis and reproducible research. · Experience with
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foundation in computational or statistical genetics. Experience analyzing large-scale datasets is essential, as the work will involve complex genomic and multi-omics data. Familiarity with machine learning
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply