美国马里兰大学全球农业监测研究中心博士后

　　美国马里兰大学全球农业监测研究中心博士后

　　Position Number:119630

　　Title:Post-Doctoral Associate

　　Functional Title:Post-Doctoral Associate

　　Category Status:15-Fac.Non-Tenured,Continuing Con

　　Applicant Search Category:Faculty

　　University Authorized FTE:100

　　Unit:BSOS-Geography

　　Position Summary/Purpose of Position:The University of Maryland’s Center on Global Agricultural Monitoring Research is seeking an outstanding researcher at the Post-doctoral associate or Assistant Research Professor 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: https:// 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. Applications from women and minorities are particularly sought. The University of Maryland is an Equal Opportunity Affirmative Action Employer.

　　Minimum Qualifications:A PhD in computer science, geographical sciences, remote sensing, agricultural sciences, physics, engineering, mathematics, or related fields.

　　Preferences:

　　Additional Certifications:

　　Additional Information:Candidates must be able to provide proof of eligibility to work in the USA. The salary is commensurate with experience.

　　Posting Date:05/28/2020

　　Closing Date:

　　Open Until FilledYes

　　Best Consideration Date06/30/2020

　　Physical Demands

　　Diversity 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.

　　Applicant Documents

　　Required Documents

　　  Cover Letter

　　  Curriculum Vitae

　　  List of References (no emails sent from system)

　　  Research (examples: research statement, research programs)

　　Optional Documents

　　  Writing Sample 1