24 structural-engineering "https:" "https:" "UCL" "UCL" Postdoctoral positions at Texas A&M AgriLife
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practice. Responsive agriculture integrates data, technology, and management practices to make production systems more resilient, profitable, and adaptable to changing environmental, resource, and market
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crop improvement. The successful candidate will work on chromosome-scale genome assembly, gene annotation, structural variation discovery and development of genomics tools to accelerate breeding across
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duties as required. Required Education: -Ph.D. degree in chemistry, environmental science, environmental engineering and other relevant areas. Preferred Experience: -Hands-on experience of non-target
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-funded interdisciplinary research project focused on social media use and mental health of adolescents from representative racial and/or ethnic minority groups. Led by Dr. Jun Wang (https://alec.tamu.edu
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, and the Texas A&M AgriLife onion projects • Conduct whole genome structural and functional analysis in vegetable crops • Manage marker-assisted selection in vegetable crops and collect plant
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, exercise physiology, health communications, public health, social sciences, life sciences, engineering, data and computation science, and economics. Healthy Living implements, evaluates, and disseminates
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, environmental chemistry, environmental engineering, biological and agricultural engineering or closely related field Preferred Experience: • Strong background and research experience in soil chemistry and soil
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Job Title Postdoctoral Research Associate Agency Texas A&M Agrilife Research Department Biological & Agricultural Engineering Proposed Minimum Salary Commensurate Job Location College Station, Texas
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: -Ph.D. in biological, chemical, or physical sciences Preferred Experience: -Experience in a molecular biology, biochemistry, or structural biology lab Required Special Knowledge, Skills, and Abilities
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. Familiarity with computational modeling of structure-function relationship Experience in identifying metabolites in biological samples. Sufficient knowledge in statistical analysis tools (e.g., SAS, R, XLstat