Woodwell Climate Research Center Inc-posted 2 months ago
Full-time • Entry Level
Falmouth, MA
101-250 employees

We are seeking a skilled Research Assistant to assist with two projects focused on Arctic wildfire mapping and wildfire-induced permafrost thaw data synthesis at the Woodwell Climate Research Center. This position provides an exciting opportunity to significantly advance satellite-based wildfire mapping in Alaska and contribute to assessments of post-fire permafrost thaw carbon emissions. The successful candidate will utilize high-resolution WorldView-3 imagery to enhance current mapping approaches, which typically rely on coarser-resolution Landsat and MODIS data. Leveraging advanced machine learning and deep learning techniques, the candidate will play a critical role in improving the accuracy and effectiveness of wildfire detection and monitoring. Additionally, the candidate will utilize remotely sensed and observational field data in Alaska to enhance understanding of permafrost thaw and thermokarst activity attributed to wildfires.

  • Digitize wildfires with high resolution satellite imagery for use in model training.
  • Help to develop, train, and validate machine learning and deep learning models using satellite imagery to accurately map and classify wildfire-affected areas.
  • Conduct accuracy assessments and validation to evaluate model performance and data quality.
  • Synthesize existing remotely sensed, spatial and observational data products on Yedoma permafrost landscapes in Alaska that will be used to refine a post-fire permafrost thaw carbon emissions model.
  • Participate in possible field campaigns to fill observational data gaps related to post-fire thermokarst activity and resulting carbon emissions.
  • Prepare visualizations, maps, and reports detailing methodologies, results, and implications for wildfire mapping and patterns of post-wildfire permafrost thaw.
  • Collaborate closely with project lead and research partners to ensure alignment of methodologies and project objectives.
  • Present research findings at internal meetings, external conferences, and contribute to manuscript preparation for peer-reviewed publications.
  • Manage and organize large geospatial datasets, ensuring data integrity, documentation, and accessibility.
  • Participate in regular project meetings and assist with reporting project progress to funding agencies.
  • Demonstrated experience using remote sensing (MAXAR or Landsat preferred) or other Earth observation data, and advanced statistical techniques.
  • Knowledge of Geographic Information Systems (GIS) such as ArcGIS or QGIS.
  • Knowledge of forest and disturbance dynamics.
  • Advanced computational and programming skills, preferably with python or R.
  • Experience with ecological field observations.
  • Excellent written and oral communication skills.
  • Ability to work independently and in a highly collaborative environment.
  • Generous benefits package
  • Work-life balance
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