Post-Doc, Asst Research Prof or Assoc Research Prof

The University of Maryland Center on Global Agricultural Monitoring Research is seeking an outstanding researcher at the Post-doctoral associate, Assistant Research Professor, or Associate Research Professor level, with a strong interest in machine learning and agriculture to join a diverse team working on computer vision and signal processing applications for agricultural monitoring (satellite imaging) and food security, within the framework of the NASA HARVEST Consortium, led by Inbal Becker-Reshef at UMD’s Center for Global Agricultural Monitoring. HARVEST is a 5-year initiative focused on advancing the use of earth observations applications for food security and agricultural markets, with a diverse set of over 40 national and international partners (http://www.nasaharvest.org).

The successful candidate will work on research related to machine learning applications to crop production forecasting for the major food producing countries, as well as for those countries most at risk to food insecurity at the field to global scales. This will involve developing models to forecast crop yields, map crop types, and alert of impending crop shortfalls, to name a few, in order to inform key agricultural and food security decisions by a range of public and private stakeholders. This research will be carried out through the use of a wide range of satellite data (including MODIS, Landsat, Sentinel-1, Sentinel-2 ) unique ground collected data-sets, global archives of diverse socio-economic data and statistics.

A successful applicant should hold a PhD in computer science, remote sensing, agricultural sciences, physics, engineering, mathematics, or related fields. A strong programming background (especially Python, R, IDL, or C++) and an interest in agriculture and food security research and applications is required and experience with working the Google Earth Engine is a plus. The candidate will be expected to work well within a diverse team and to design and lead projects that will contribute to the overall aim of the HARVEST Consortium as well as work on ongoing activities.

Interested candidates should send a CV, short cover letter (1 page) expressing your motivation to apply, and contact information for three references.