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Field
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accurate completion. Algorithm Design: Design and implement algorithms for tensor completion, considering the unique challenges posed by sparse and multidimensional network data. This involves developing
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modes (e.g., HCCI) for net-zero fuels like hydrogen and ammonia. A key innovative pillar is the development of an AI-driven control strategy. Machine learning algorithms, including reinforcement learning
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about related social, ethical, political, and economic impacts; Developing, deploying, and evaluating digital technologies in applications across diverse sectors critical to national security and societal
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, array data, propagation data. Develop processing algorithms and assess their performance. Interpret results. Implement research grade software and analysis tools in Matlab including underwater
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institutions from academia and industry in multiple research projects. What you will do Development & application of innovative algorithms in the field of machine learning, specifically with focus on decision
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-sensitive data augmentation and mining Manage multiple stakeholders, meet deadlines, and integrate project outputs into DeltaXignia’s workflows with training Balance technical development and commercial goals
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Support for testing, data analysis, and data display Contribute to the research and development of unique algorithmic solutions for a wide array of sponsor requirements, with a focus on machine learning and
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authorized DoD SkillBridge partner and welcomes all transitioning military members to apply. You will: Design and conduct exploratory data analysis and hypothesis testing to support analytic objectives Develop
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site-specific and realistic radio propagation data through GPU-accelerated ray tracing to train AI/ML algorithms. Exploring the use of generative models for wireless channel modeling, e.g., to produce
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on developing novel ML algorithms, enhancing human-AI collaboration, and exploring systems tailored to dynamic, human-centered environments. They may also work with diverse signal modalities, including vision