The Department of Geographical Sciences at the University of Maryland College Park is currently looking to fill several Professional Track Research Faculty positions These non tenure opportunities are open at the levels of Postdoctoral Associate or Assistant Research Professor based on the successful candidates qualifications and experience We offer highly competitive salaries and benefits packages The roles encompass a broad spectrum of activities including but not limited to supporting projects linked to the Global Ecosystem Dynamics Investigation GEDI httpsgediumdedu NASAs Carbon Monitoring System CMS httpscarbonnasagovcms and development of methods for mapping and monitoring mature and old growth forestsThe GEDI mission focuses on biomass estimation biodiversity habitat characterization forest complexity and prognostic ecosystem models and is slated to resume operations in late 2024 for a minimum of three years An important aspect of our current initiatives focuses on the integration of GEDI data with other Earth Observation EO data such as from passive opticalstereo and Synthetic Aperture Radar SAR technologies The latter includes data from TanDEM X ALOS 2 and Sentinel 1 as well as the forthcoming NISAR and BIOMASS missions Successful candidates will participate in diverse aspects of GEDI related science analyses and projects This participation includes refining and validating science algorithms post flight calibration and validation developing field observation databases science data product development and the fusion of multi sensor data There is also the opportunity to utilize these remote sensing data in science investigations within the candidates areas of interestOur NASA CMS projects are focused on combining GEDI and interferometric SAR InSAR data to map high resolution biomass and its changes in collaboration with partner institutions including the German Aerospace Center DLR alongside activities utilizing these data to drive ecosystem and diversity models Our mature and old growth forest work is in partnership with the US Forest Service NASA Goddard Space Flight Center GSFC and Harvard Forest This research is developing methodologies for the assessment and monitoring of mature and old growth forests using a comprehensive range of EO data modeling and in situ national forest inventory data These projects have significant engagement with stakeholders at the local national and international levelsIdeal candidates will have a background in fields related to Earth observation and terrestrial ecology with demonstrated interests in remote sensing science machine learning ecosystem structure and biomass ecosystem modeling and studies on habitatdiversity among others Technical expertise in lidar terrestrial airborne or spaceborne andor SAR remote sensing is highly desirable Nonetheless applicants with strong backgrounds in other remote sensing domains or those skilled in applying machine learning or statistical analyses to remote sensing data are also welcome to apply