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including use of simple to complex statistical analysis . •Compose and write scientific publications, progress and annual/final reports for grants. •Supervise undergraduate and/or graduate students and other
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data analytics, statistical analysis. -Develop a breeding pipeline that incorporates genomic, Phenomic and Enviromic data to implement a predictive-based breeding scheme. -Complete statistical analysis
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researchers and projects. Engage with agency, industry, academic partners. Assist with mentoring of graduate students. Other duties as required. Required Education: PhD in Wildlife Ecology, Wildlife Management
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Experience: PhD in reproductive biology, cell and developmental biology, genetics, or similar field Molecular biology experience. Animal research Conducting statistical analyses. Preferred Education and
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Education and Experience PhD in related field (e.g., Kinesiology, Public Health, Psychology). Required Knowledge, Skills, and Abilities Appropriate research background, as demonstrated by publications in peer
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for this position prior to your doctoral degree being conferred, please attach a letter from your school’s official Graduate Office, Registrar’s Office or PhD Committee Chair certifying that all requirements
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) • Evaluate data and summarize results for preparation in peer reviewed publications including use of simple to complex statistical analysis • Compose and write scientific publications, progress and annual
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including use of simple to complex statistical analysis . •Compose and write scientific publications, progress and annual/final reports for grants. •Supervise undergraduate and/or graduate students and other
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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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analysis skills: Statistical analysis through SPSS, R, Design Expert, Origin, MATLAB, chemometric tools, or other software. Bioinformatics and grant writing. All positions are security-sensitive. Applicants