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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 2 hours ago
Dynamics Investigation (GEDI) and ECOSTRESS instruments with Sentinel and Landsat time series to characterize vegetation structure, ecosystem water stress, wildfire severity, and post-fire recovery. Research
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 12 hours ago
demonstration of experience in quantitative research. PREFERRED: Experience with machine learning methods for time-series analysis; anomaly and changepoint detection, or instrument diagnostics; familiarity with
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. Appointments in this series are intended to provide a period of advanced training and professional development in preparation for independent careers. Initial appointments are typically for a two-year term
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for advanced statistical and time-series analyses. They will analyse behavioral, EEG and eye-tracking data collected during prolonged experimental sessions. The research will focus on the modelling and
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learning from limited data, cross-sensor integration, and scalable reasoning over large-scale time-series data, with applications in disaster response, urban analytics, and environmental monitoring. The team
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About the role Applications are invited for a Postdoctoral Research Associate in molecular lanthanide chemistry to work under the supervision of Professor Michael Neidig for a period of up to 3
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, conferred by the position start date. Demonstrated research experience in cancer biology, developmental biology, tissue engineering, mechanobiology, or a closely related area. Experience with mammalian cell
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profiling approaches. Experience working with human tissue, particularly formalin-fixed, paraffin-embedded (FFPE) tissue. Experience with RNA sequencing, transcriptomic analysis, or other high-dimensional
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includes the opportunity for three weeks of training in higher education teaching and learning. The postdoctoral fellow will: Develop and maintain harmonized satellite time-series datasets (Landsat and
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other field or laboratory instrumentation Apply appropriate behavioral, statistical, econometric, causal, spatial, machine learning, deep learning, computer vision, time-series, or mixed-methods