Postdoctoral Associate/Assistant Research Professor
Job Description
Position Number:
129185Title:
Open RankFunctional Title:
Postdoctoral Associate/Assistant Research ProfessorCategory Status:
15-Fac.Non-Tenured,Continuing ConApplicant Search Category:
FacultyUniversity Authorized FTE:
1Unit:
BSOS-GeographyCampus/College Information:
Founded in 1856, University of Maryland, College Park is the state’s flagship institution. Our 1,250-acre College Park campus is just minutes away from Washington, D.C., and the nexus of the nation’s legislative, executive, and judicial centers of power. This unique proximity to business and technology leaders, federal departments and agencies, and a myriad of research entities, embassies, think tanks, cultural centers, and non-profit organizations is simply unparalleled. Synergistic opportunities for our faculty and students abound and are virtually limitless in the nation’s capital and surrounding areas. The University is committed to attracting and retaining outstanding and diverse faculty and staff that will enhance our stature of preeminence in our three missions of teaching, scholarship, and full engagement in our community, the state of Maryland, and in the world.
Background Checks
Offers of employment are contingent on completion of a background check. Information reported by the background check will not automatically disqualify you from employment.
Position 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) [https://gedi.umd.edu], NASA’s Carbon Monitoring System (CMS) [https://carbon.nasa.gov/cms/], and 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. 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 candidate’s areas of interest.
Our 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 U.S. 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 levels.
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, among others. 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.
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. 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 candidate’s areas of interest.
Our 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 U.S. 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 levels.
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, among others. 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.
Benefits Summary
Top Benefits and Perks:Minimum Qualifications:
Education:
- 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:
Preferences:
- Experience with lidar remote sensing using GEDI data
- Experience with SAR remote sensing
- Experience 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.
● 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:
02/20/2024Open Until Filled
YesBest Consideration Date
03/30/2024Diversity Statement:
The University of Maryland, College Park, an equal opportunity/affirmative action employer, complies with all applicable federal and state laws and regulations regarding nondiscrimination and affirmative action; all qualified applicants will receive consideration for employment. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, religion, sex, national origin, physical or mental disability, protected veteran status, age, gender identity or expression, sexual orientation, creed, marital status, political affiliation, personal appearance, or on the basis of rights secured by the First Amendment, in all aspects of employment, educational programs and activities, and admissions.
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