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Field
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/diseases, nutrient/health status applications. Build robot-cloud collaborative platforms supporting real-time data compression and edge AI model updates. Lead national, international, and industry
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characterization: Implementation of quasi-static, creep, and fatigue tests (tensile, compression, bending, shear), with instrumentation (extensometry, imaging), non-destructive testing methods, and dynamic
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/algorithms for payload data products, image processing and optical payload data compression. Contribution to mission performance assessment and to data products quality monitoring and improvement. You are
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sustainable machine learning approaches and addressing renewable energy related projects. Likewise, deploying a novel paradigm of KGML (knowledge guided machine learning) can propel further research. PhD
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geometry, temporal generalization). Computational measures of visual information (e.g., image statistics/compressibility proxies, deep network features, object/scene representations). Position Summary
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, intracranial pressure waveforms, thermodilution-derived cerebral blood flow, cerebral microdialysis, cardiopulmonary vital signs, brain imaging and unstructured text datasets. This position offers opportunities
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computing, data analysis and visualization, computational imaging and spectroscopy, AI and compressive sensing, and quantum computing to develop robust solutions that bridge theoretical frameworks with real
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Demonstrated skills in digital manipulation of images and video, including resizing, compressing, converting and rendering a variety of media into common digital formats Excellent written and organizational
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evaluation, and technical advisory. Position Summary As an Assistant Machine Learning Engineer in the Frontier Lab, you will be a technical contributor supporting applied AI research, prototype development
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research and prototype capability development for government and DoW missions. This role spans the research-engineering spectrum: some SR MLRS hires may lean more research-heavy and others more engineering