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such as landslide movement style, runout, and how landslide hazards evolve over time. This Ph.D. project will leverage the analysis of new time-series data from cloud-based satellite image archives
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Stem Cell Biology. Experience in lab management and biosafety regulations. The appointment will be in the Project Scientist series and is a non-Senate position. Academic rank & step will be commensurate
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environmental variables to develop LUE, WUE and canopy conductance function for diagnostic mapping of forest ecosystem functioning metrics. We will apply time-series analysis to investigate seasonal and
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series, and multiple retreats and programming events that collectively enable robust interactions among basic, translational, and clinical immunologists. The Department of Immunology is ranked 7th in
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Research and Innovation, the successful candidate will work on the project "Regulatory Compliance in Digital Financial Services from an Information Systems Perspective" (ReFIS). The rise of digital financial
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nature-based solution opposed to traditional ‘grey’ engineering, offer catchment-level solutions by using natural processes to slow and store water through a series of diffused interventions. Historically
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, energy-related datasets. Proficiency in Python, MATLAB, and/or Julia for modeling, simulation, and data analysis. Familiarity with GIS tools (e.g. QGIS), time-series databases (e.g. InfluxDB), and version
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interdisciplinary research and training environment with specialized seminar series and tech talks and training courses that develop both scientific and complementary skills. As a 4R-RTG PhD student, you will be
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part of a vibrant interdisciplinary research and training environment with specialized seminar series and tech talks and training courses that develop both scientific and complementary skills. As a 4R
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processing, time series analysis or machine learning for the interpretation of structural data is desirable. Basic knowledge of numerical analysis and design of structures for special load cases (earthquakes