Sort by
Refine Your Search
-
Listed
-
Field
-
Research Institute Program and will focus on grapevine and pecan, two of the most economically important crops in Texas. Job Responsibilities: 30% Lead greenhouse experiments on nanoplastics and PFAS uptake
-
Sciences at Texas A&M University Texas A&M Forest Service Texas A&M Veterinary Medical Diagnostic Laboratory As the nation’s largest most comprehensive agriculture program, Texas A&M AgriLife brings together
-
Description Responsibilities: Develop and manage research projects related to dairy health and management. Collect, organize, and analyze data from dairy herds using advanced statistical and computational tools
-
microbial influences on fire ant behavior - Collect, analyze, and archive research data; establish and maintain databases; and utilize computational tools for data analysis - Perform experiments to evaluate
-
Sciences at Texas A&M University Texas A&M Forest Service Texas A&M Veterinary Medical Diagnostic Laboratory As the nation’s largest most comprehensive agriculture program, Texas A&M AgriLife brings together
-
Sciences at Texas A&M University Texas A&M Forest Service Texas A&M Veterinary Medical Diagnostic Laboratory As the nation’s largest most comprehensive agriculture program, Texas A&M AgriLife brings together
-
members to support ongoing research projects. Perform other related duties as needed to support the research program. Required Education: Ph.D. in Horticulture or a related field. Preferred Experience
-
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
-
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
-
. 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