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: U.S. Citizen Only Degree: Doctoral Degree received within the last 36 month(s). Discipline(s): Computer, Information, and Data Sciences (6 ) Life Health and Medical Sciences (4 ) Mathematics and
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cultivated and non-crop plant species. Although many native plants, cover crops, and beneficial vegetation provide valuable ecosystem services, including pollinator resources, biological control habitat
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to kinetic and/or non-kinetic weapons effects Gain experience with diagnostic instrumentation development, gauge ranging, and analyzing test data Learn how to evaluate test results and document findings
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: Under the guidance of a mentor, you will be trained to: Develop novel components to integrated pest systems that improve pest and disease control while maintaining plant productivity. Co-develop effective
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to develop various pre-, post-, and in-situ processes; to analyze ex-situ data; and to implement additive tool motion path controls. The desired digital manufacturing research competencies include computer
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the opportunity to learn to: Understand the general process of a soybean breeding program Practice field-based techniques (e.g., planting, controlled pollinations, observational data collection
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of the relevant fields. Preferred skills: Preferred educational background in computer sciences or related field. Any educational or work experience with agricultural data is a plus. Knowledge in computer
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skills: Preferred educational background in computer sciences or related field. Any educational or experience with agricultural data is a plus. Knowledge in computer programming (Python, HTML, Java
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Organization Centers for Disease Control and Prevention (CDC) Reference Code CDC-2026-0004 How to Apply To submit your application, scroll to the bottom of this opportunity and click APPLY. A
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Organization Centers for Disease Control and Prevention (CDC) Reference Code CDC-2026-0007A How to Apply To submit your application, scroll to the bottom of this opportunity and click APPLY. A