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; Contemporary quantitative experience in comparative zoology or population genomics. Required knowledge, skills and abilities: Good communication and computer skills. Ability to multi task and work cooperatively
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software for genetic analysis of polyploid plant species, and ability to work with databases and to handle large data sets. Experience in phylogenetic analysis, marker trait association studies and genomic
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Type Staff Job Description Major/Essential Duties of Job: 1. Develop machine learning or physical based models for plant water stress quantification. 2. Develop machine learning models for crop mapping
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. Click here to learn more about how you can be a part of AgriLife and make a difference in the world! Position Information: Texas A&M AgriLife Research is seeking applications for a Postdoctoral
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contaminated sites. Supervise technicians and undergraduates. Coordinate research activities with a large team of collaborators. Present data in scientific meetings. Prepare manuscripts for publication. Research
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AgriLife is uniquely positioned to improve lives, environments and the Texas economy through education, research, extension and service. Click here to learn more about how you can be a part of AgriLife and
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of programming or scripting languages such as Python, Fortran, R or others. Experience in remote sensing data analysis and geographic information systems. Experience in machine learning motivated algorithms and
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Agriculture (CEA) Engineering Lab as a Postdoctoral Research Associate. The candidate will primarily work in one or more of the following areas: computer vision, AI-driven automation, and/or robotics
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in sorghum. Required knowledge, skills and abilities: -Ability to multi-task and work cooperatively with others -Good communication and computer skills Preferred licenses and certifications: -Valid
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publications. Qualifications Required Education and Experience: PhD degree in any of the following: plant biology, plant physiology, analytical chemistry, genetics, biotechnology, food science, or other closely