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Field
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transport problems across the fission and fusion energy fields. These areas include application of cutting-edge high performance computing algorithms, workflows, and methods to solve problems related
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runoff under climate change, and Analyze changes in marine ecological (phytoplankton) communities during and after freshwater extremes (low-salinity pulses) at multiple spatial and temporal scales
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algorithms and system interfaces for MuFIN, as well as interfaces for stakeholder participation in PartiMeas. Conduct software testing and debugging to ensure performance and scalability. Perform other duties
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cooperative, competitive, and mixed settings. Collaborative decision-making frameworks and decentralized learning algorithms. Adaptive, meta-learning, and context-aware strategies to enhance policy
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of approximately 1.7 million square feet and high-performance computing facilities at the DOD Supercomputing Research Center. This opportunity has multiple projects based out of the ERDC Field Research Facility in
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Figma. Leverage open-source and internal frameworks to support network operations. Independently analyze complex issues, evaluate multiple factors, and write maintainable software based on user stories
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algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with
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Science Specialist will: 1) review empirical data and algorithms applied to the price, end-use, fishing effort and layer 3 databases and develop code that imputes missing data to complete gaps in
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. This position requires developing bioinformatics pipelines, applying variant interpretation algorithms, project management skills and communicating with diverse stakeholders to gather and articulate requirements
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control, state estimation, and path planning algorithms for single and multi-agent robotic systems (UAVs). develop and train AI models for practical applications such as real-time object detection and