University of Maryland
Postdoctoral Associate/Assistant Research Professor
University of Maryland, College Park, Maryland, us, 20741
Postdoctoral Associate/Assistant Research Professor
Functional Title:
Postdoctoral Associate/Assistant Research ProfessorCategory Status:
15-Fac.Non-Tenured,Continuing ConApplicant Search Category:
FacultyUniversity Authorized FTE:
1Unit:
BSOS-GeographyPosition Summary/Purpose of Position:
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 candidate’s 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) and NASA’s Carbon Monitoring System (CMS), as well as the development of methods for mapping and monitoring mature and old-growth forests.The 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 optical/stereo and Synthetic Aperture Radar (SAR) technologies. Successful candidates will participate in diverse aspects of GEDI-related science analyses and projects, including 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.Ideal 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 habitat/diversity. Technical expertise in lidar (terrestrial, airborne, or spaceborne) and/or 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.Minimum Qualifications:Candidates must possess a doctoral degree in Geographical Sciences or a related field within environmental science, such as Biology or Forestry.Those with doctoral degrees in other disciplines (e.g., Physics, Computer Science, Electrical Engineering) who demonstrate substantial knowledge and understanding of land surface remote sensing are also eligible.Knowledge, Skills, and Abilities:Essential skills include competency in programming and statistical analysis, with experience in languages and tools such as Python, IDL, MATLAB, C/C++, R, PyTorch, TensorFlow.For the Assistant Research Professor level, a proven track record of independent research and peer-reviewed publications is required.Preferences:Experience with lidar remote sensing using GEDI dataExperience with SAR remote sensingExperience and expertise in working effectively with individuals from diverse backgrounds.Additional Information:
To apply through ejobs, you will need to provide:A personal statement detailing background and experience relevant to the role.A current, signed, and dated Curriculum Vitae.Reprints or URLs for selected peer-reviewed publications (upload as “writing sample 1” in required documents).Contact details (including email addresses) for 3-5 references.Candidates are encouraged to reach out to Ralph Dubayah (dubayah@umd.edu) for discussions on potential research interests they wish to pursue at the University of Maryland.Posting Date:
02/20/2024Closing Date:
Open Until FilledBest Consideration Date:
03/30/2024The University of Maryland, College Park, is an equal opportunity/affirmative action employer, complying with all applicable federal and state laws and regulations regarding nondiscrimination and affirmative action.
#J-18808-Ljbffr
Functional Title:
Postdoctoral Associate/Assistant Research ProfessorCategory Status:
15-Fac.Non-Tenured,Continuing ConApplicant Search Category:
FacultyUniversity Authorized FTE:
1Unit:
BSOS-GeographyPosition Summary/Purpose of Position:
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 candidate’s 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) and NASA’s Carbon Monitoring System (CMS), as well as the development of methods for mapping and monitoring mature and old-growth forests.The 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 optical/stereo and Synthetic Aperture Radar (SAR) technologies. Successful candidates will participate in diverse aspects of GEDI-related science analyses and projects, including 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.Ideal 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 habitat/diversity. Technical expertise in lidar (terrestrial, airborne, or spaceborne) and/or 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.Minimum Qualifications:Candidates must possess a doctoral degree in Geographical Sciences or a related field within environmental science, such as Biology or Forestry.Those with doctoral degrees in other disciplines (e.g., Physics, Computer Science, Electrical Engineering) who demonstrate substantial knowledge and understanding of land surface remote sensing are also eligible.Knowledge, Skills, and Abilities:Essential skills include competency in programming and statistical analysis, with experience in languages and tools such as Python, IDL, MATLAB, C/C++, R, PyTorch, TensorFlow.For the Assistant Research Professor level, a proven track record of independent research and peer-reviewed publications is required.Preferences:Experience with lidar remote sensing using GEDI dataExperience with SAR remote sensingExperience and expertise in working effectively with individuals from diverse backgrounds.Additional Information:
To apply through ejobs, you will need to provide:A personal statement detailing background and experience relevant to the role.A current, signed, and dated Curriculum Vitae.Reprints or URLs for selected peer-reviewed publications (upload as “writing sample 1” in required documents).Contact details (including email addresses) for 3-5 references.Candidates are encouraged to reach out to Ralph Dubayah (dubayah@umd.edu) for discussions on potential research interests they wish to pursue at the University of Maryland.Posting Date:
02/20/2024Closing Date:
Open Until FilledBest Consideration Date:
03/30/2024The University of Maryland, College Park, is an equal opportunity/affirmative action employer, complying with all applicable federal and state laws and regulations regarding nondiscrimination and affirmative action.
#J-18808-Ljbffr