The University of Texas at Austin · 5 hours ago

Postdoctoral Fellow in Remote Sensing Environmental-Social Change

Austin, TX

Full-time

Remote

New Grad, Entry Level

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Responsibilities

Work with remote sensing datasets, including Landsat and high-resolution products. Apply data analytics and machine learning techniques to map and interpret data using geoprocessing tools and GIS platforms, including Google Earth Engine and ArcPy. Map the evolution of colonias over time and analyze social and environmental stressors, including floods, on resident populations.

Contribute to publication of scientific papers, present findings at scholarly meetings, and coordinate with stakeholders.

Collaborate with research program team members and participate in program development through proposals and other fund raising.

Provide support and service, as needed, to the supervisor, BEG, and the Jackson School, when possible.

Qualification

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Remote SensingData AnalyticsMachine LearningPythonRMatlabArcGISQGISGoogle Earth EngineGeoprocessingHydrologyEnvironmental ScienceData WranglingStatistical AnalysisDeadline Management

Required

Ph.D. awarded May 2022 or later in Earth Science (e.g. Hydrology, Hydrogeology, Geology, Geography), Civil Engineering, or closely related field.

Expertise in remote sensing data products and their environmental applications.

Proficiency in data wrangling, analytics, synthesis, and management.

Knowledge of machine learning approaches, programming languages (e.g., Python, R, Matlab) and geoprocessing analytics (e.g., ArcGIS, QGIS, Google Earth Engine).

Adaptability to apply skills in environmental data analytics to other topics related to water resources and the environment.

Proven ability to effectively disseminate project results to peers and stakeholders.

Experience working within an integrated team of scientists, engineers, and economists in a dynamic environment.

Experience meeting deadlines.

Excellent written and oral communication skills.

Professional demeanor and excellent interpersonal skills.

Degree must have been obtained within 3 years from date of hire.

Preferred

Project relevant experience and demonstrated aptitude with: (a) assembling and synthesizing disparate remote sensing products for mapping building/infrastructure development, (b) assessing vulnerability to environmental hazards such as flooding, (c) artificial intelligence/machine learning techniques applied to mapping urban development, land cover change, building footprints, and flood exposure.

Familiarity with social vulnerability metrics.