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, modeling, or AI/ML approaches in agricultural or environmental research. -Proficiency in server administration, distributed computing, and cloud platforms (AWS, Azure, Google Cloud). -Knowledge of full-stack
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technologies, including big data analytics, artificial intelligence (AI), remote data transfer, and cloud computing to help solve complex agricultural problems. -The candidate will work on the synthesis
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will have the opportunity to contribute to developing educational outreach materials, mentor undergraduate and graduate students, and participate in grant writing. Required Education and Experience: PhD
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agencies. -Opportunity to participate in mentoring of students. -Other duties as required. Required Education: -PhD in Entomology or related field Preferred Experience: - Experience with chemical/molecular
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-microbe-pathogen interactions. -Maintain detailed laboratory records and organize computational work in the cloud. -Write manuscripts and take the lead in publishing scientific data in peer-reviewed
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management. The researcher will work with department faculty and graduate students with the work under the supervision of Dr Simon Somogyi. The successful applicant will be responsible for the development of a
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metabolites, biomarkers, and micronutrients derived from human, animal, and plant research. The Responsive Agriculture Program is closely connected to the Human Behavior Laboratory, a leading facility equipped
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Description The Postdoctoral Research Associate is responsible for designing, conducting, and summarizing research projects associated with dairy cattle heat stress experiments and develop associated computer
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comprehensive agriculture program, Texas A&M AgriLife brings together a college and four state agencies focused on agriculture and life sciences within The Texas A&M University System. With over 5,000 employees
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data and create individual reports for landowners Publish scientific manuscripts and present research at scientific conferences Other duties as required. Required Education: PhD in rangeland management