36 computational-physics-postdoc-"https:" "Caltech" Postdoctoral positions at Texas A&M AgriLife
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, computational biologists, and industry partners. The postdoc will also have opportunities for professional development, grant writing, and mentorship experience to support an independent career path. All
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. The position will involve designing and analyzing experiments, modeling producer and consumer behavior, and integrating experimental and observational approaches to generate robust evidence. The postdoc will
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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
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Staff Job Description Job Responsibilities 50%: Lab research - Design, plan, conduct and coordinate experiments in a wet lab as well as using computers. 20%: Communication - Keep detailed records of data
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with process-based models, including APEX, SWAT, EPIC, DayCent, or DNDC. Proficiency in computer programming, including scripting in Python, Fortran, or other computing tools for data processing and
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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
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Description The Postdoctoral Research Associate will examine the epigenetic regulation of the paternal genome and subsequent role in embryo development in the Luense Lab (https://animalscience.tamu.edu/people
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promotion, food access, food systems, food and nutrition insecurity, dietary patterns and behaviors, diet/food interventions, program development and evaluation, physical activity behaviors and intervention
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approaches for ecological and paleontological data. Other requirements or other factors: Position requires collaboration and coordination across multiple institutions. Postdoc must be resident at Georgia Tech
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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