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both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates
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rolling basis with start dates as early as 1/1/2026 and as late as 3/1/2026. Group or Departmental Website: https://simpsoba.su.domains/ (link is external) How to Submit Application Materials: Please upload
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. In this position, your primary task will be to lead the development of algorithms, software, and hardware to extend the current HAUCS framework. This includes developing the sensors, sensing robotic
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systems. The candidate will be responsible for processing repeat pass inSAR data and implementing efficient data calibration algorithms based on heterogeneous spatial sampling of ground truth points
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of all-sky microwave radiance assimilation algorithm are highly encouraged. Field of Science: Earth Science Advisors: Zhu, Yanqui (301) 614-5844 yanqiu.zhu@nasa.gov Applications with citizens from
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of radiance data from new hyperspectral infrared instruments such as IASI-NG, MTG-IRS Enhancement of CrIS radiance assimilation algorithm are highly encouraged. - Use machine learning methods to cope with model
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retrieval algorithm development with focus on using the polarimetric signals, the new FIR or sub-mm bands, and/or the ML/AI approach; (3) ML/AI application on system/pattern tracking on satellite images
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include remote sensing algorithm development, modeling studies, data fusion, sensor development, and/or snow satellite mission concept studies. Participation in the design and execution of field campaigns
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following areas: Strong foundation in machine learning, optimization, and deep learning algorithms, including Transformer architectures. Hands-on experience or solid theoretical knowledge of LLMs/SLMs
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reconstruction algorithms to relax the need for highly uniform magnetic field to conduct MRI scanning, and by doing so, to enable next generation MRI scanners to be far less expensive, ultracompact, and