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the opportunity to develop their own research algorithms suitable for use with SBG-like datasets. This is a unique and rare opportunity for an early-career scientist to advance their research interests
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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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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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developing light curve detrending and transit search algorithms. For each of these areas, we anticipate opportunities to work with current data and to obtain new observations of transiting exoplanets with
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opportunity would be most suitable for an individual: with significant experience manipulating or developing scientific applications with programming languages for thermal modeling and planetary data analysis
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System modeling - Statistics and data science (especially, multivariate statistics, Bayesian statistics) - Remote sensing theory (e.g., radiative transfer physics; algorithm development) - Remote sensing
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are not limited to: Learn research techniques to develop algorithms and models for the simulation of field data Participate in experimental activities such as research design, data collection, technical
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are not limited to: Learn research techniques to develop algorithms and models for the simulation of field data Participate in experimental activities such as research design, data collection, technical
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ratios. Once we have developed the algorithm we can then adapt it to broadly apply to a wide range of invasive arthropod and tick species. Protein-to-DNA alignments and gene prediction will be conducted
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technologies required to make that future possible. We’ve long touted our success in developing the technologies that took on acid rain in the 1970s and mercury in the early 2000s. Program Goals The NETL