Faculty Assistant (GIS/Remote Sensing); College Park, MD

Updated: over 2 years ago
Location: College Park, MARYLAND
Deadline: 31 Dec 2021

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Agency
University of Maryland
Location
College Park, MD
Job Category
Post Doctoral Appointments
Salary
DOE
Last Date to Apply
12/31/2021
Description
The Department of Environmental Science and Technology will soon post a job description for a full time Faculty Assistant. If interested in being notified when the full job posting is released, please contact Dr. Jyoti Jennewein at [email protected] with the subject line: “Interest in UMD Faculty Assistant Position”. Background: This position will provide remote sensing, soil landscape analysis, and geospatial analysis support for the Precision Sustainable Agricultural team (national network of sustainable agriculture scientists), and numerous private partners. The candidate will work with a team of applied agricultural scientists, technologists, and data scientists to assess cover crop and weed dynamics and crop water stress in agronomic cropping systems using a suite of remote sensing systems (satellite, airborne, UAV, tractor-mounted, field deployed) and soil landscape analysis techniques (digital soil mapping, spatial disaggregation, SSURGO analysis). The candidate will assess cover crop performance and weed presence spatially to inform decision support tools, modeling efforts, and precision technologies. Note: position details may be altered in the final job posting. Key partners/mentors will include: Dr. Brian Needelman, Department of Environmental Science and Technology, University of Maryland, College Park, MD 20742, [email protected], 301-405-8227 Dr. Steven Mirsky, USDA-ARS Sustainable Agricultural Systems Laboratory, Beltsville, MD, [email protected], 240-304-9479 Dr. Dean Hively, USGS stationed at USDA-ARS Hydrology and Remote Sensing Laboratory, Beltsville, MD, [email protected], 301-504-9031 Dr. S. Chris Reberg-Horton, Department of Crop and Soils, North Carolina State University, Raleigh, [email protected], 919 515-7597 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. EEO/AA Statement The University of Maryland, College Park is an Equal Opportunity/Affirmative Action Employer; all qualified applicants, including veterans and people with disabilities, will receive consideration for employment. UMD is actively engaged in recruiting, hiring, and promoting underrepresented communities.
Qualifications
Required job qualifications: • PhD in applied agricultural or soil science, spatial statistics, landscape ecology, data science, remote sensing or related field. • Expertise and experience in processing and analysis of remotely sensed data (optical, radar, lidar, etc.). • Ability to process and analyze soil survey data and perform terrain analysis and digital soil mapping. • Demonstrated ability to deliver and communicate scientific results and concepts. • Established research credentials through publications in relevant refereed journals, and an existing record of, or strong potential for, successful grant procurement. • Ability to work smoothly as part of a well-organized research collaboration. Preferred job qualifications: • Expertise and experience in processing and analysis of soil survey and topographic data. • Expertise in soil variation in landscapes, soil mapping, and soil influence on plant growth. • Experience with agricultural cropping systems and field data collection and/or analysis. • Ability to develop, debug, and revise software code: e.g. Python, SQL, IDL, JavaScript, R, and/or Bash. • Ability to migrate data streams into and out of the GIS software (e.g., ESRI, QGIS). • Working knowledge of cloud platforms (Azure, AWS or GEE). • Well-organized with strong writing and project management skills.
Contact Person
Jyoti Jennewein
Contact eMail
[email protected]

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