Home arrow Scholarships and Job offers arrow Postdoc opportunity in machine learning for remote sensing, food security
Postdoc opportunity in machine learning for remote sensing, food security
martes, 02 junio 2020

The University of Maryland’s Center on Global Agricultural Monitoring Research is seeking an outstanding researcher at the Post-doctoral associate level with strong interest in machine learning and agriculture to join a diverse team working on satellite remote sensing applications for agricultural monitoring and food security, within the framework of the NASA Harvest Program and an on-going NASA SERVIR Applied Science Team project, led by UMD’s Center for Global Agricultural Monitoring. Harvest is NASA’s Food Security and Agriculture program, focused on advancing the use of earth observations applications for food security and stable agricultural markets, with a diverse set of over 40 partners from academia, government, private, NGO and humanitarian sectors (Program Website: http://www.nasaharvest.org).

The successful candidate will work on research related to machine learning applications for crop production forecasting for smallholder agricultural systems at the field to national scales with focus on Sub-saharan Africa. This will involve developing models to map cropland, crop types, forecast crop yields 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 and develop training materials. This research will be carried out through the use of a wide range of satellite data, unique ground collected data-sets, global archives of diverse socio-economic data and statistics.

The 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 to design and lead projects that will contribute to the overall aim of the Harvest Program as well as work on ongoing activities.

Link to apply: https://ejobs.umd.edu/postings/78351<

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