USDA-ARS Improving Information Delivery Systems -Farm Management

How To Apply

To submit your application, scroll to the bottom of this opportunity and click APPLY.

• An application
• Transcript(s) – For this opportunity, an unofficial transcript or copy of the student academic records printed by the applicant or by academic advisors from internal institution systems may be submitted.  for detailed information about acceptable transcripts.
• A current resume/CV, including academic history, employment history, relevant experiences, and publication list
• Two educational or professional recommendations

All documents must be in English or include an official English translation.

Download the new ORISE GO mobile app in the Apple App Store or Google Play Store to help you stay engaged, connected, and informed during your ORISE experience and beyond!

U.S. Department of Agriculture (USDA)

USDA-ARS-NEA-

3/27/2026 3:00:00 PM Eastern Time Zone

Applications are reviewed on a rolling basis.

A research opportunity is currently available with the U.S. Department of Agriculture (USDA), Agricultural Research Service (ARS), located in Beltsville, Maryland. The Agricultural Research Service (ARS) is the U.S. Department of Agriculture's chief scientific in‑house research agency with a mission to find solutions to agricultural problems that affect Americans every day from field to table. ARS will deliver cutting‑edge, scientific tools and innovative solutions for American farmers, producers, industry, and communities to support the nourishment and well‑being of all people;

sustain our nation’s agroecosystems and natural resources; and ensure the economic competitiveness and excellence of our agriculture. The vision of the agency is to provide global leadership in agricultural discoveries through scientific excellence.

The Adaptive Cropping Systems Laboratory (ACSL) at the USDA‑ARS Beltsville Agricultural Research Center (BARC) in Beltsville, Maryland conducts integrated experimental and modeling research to understand how crops respond to key abiotic factors such as weather, soil conditions, and management practices. Our team designs and carries out controlled experiments and develops, validates, and applies advanced mathematical models to investigate a wide range of agricultural challenges, including the impacts of extreme weather on crop production, land suitability assessment, food security, on‑farm resource management, and farmer competitiveness.

Our stakeholders—including farmers and crop advisors—need clear, science‑based guidance on how to manage farming operations in response to current and projected weather and soil conditions. We are seeking an intern to continue development of an existing web‑based portable information delivery system () that integrates on‑farm data streams, ACSL crop and soil models, and weather forecasts. This toolkit is intended to provide in‑season decision support, helping end users optimize site‑specific farm management.

The participant will continue development of an existing IDS platform and support its deployment with end‑users under the guidance of laboratory mentors. Activities will include computer programming related to database development, extension of the IDS graphical user interface, and integration of our crop and soil models. Database activities will involve capturing model‑based scenario input and output data that can be queried in real time.

The participant will also collaborate with on‑site scientific staff to transition components of an existing Windows‑based graphical interface into the new web‑based IDS framework. Additional opportunities include exploring portable versions of our models and applying artificial intelligence methods to enable interaction through mobile platforms.

The participant will collaborate with an established multidisciplinary team with international expertise in crop and soil modeling, gaining knowledge about extreme weather impacts, and how crops and soils respond to genetic, environmental, and management inputs. The participant will develop new skills in computer…