10 assistant-professor-computer Postdoctoral positions at Texas A&M University System
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practices. Design and implement a "Train the Trainers" program to build the capacity of conservation professionals, NRCS field staff, and other technical service providers. Help organize a topical summit
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composition and modeling efforts to assist conservation professionals, NRCS personnel, and other stakeholders in adopting climate-smart feeding practices. Help organize a topical summit focused on feed
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Description Job Responsibilities: 50% - Utilize graphical/network models and data integrations, including work on collaborative projects. 10% - Assist in maintaining and upgrading, as necessary, our server
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, analyze data, and interpret results. -Publish research findings in peer-reviewed journals and present at professional meetings. -Assist in writing grant proposals to secure external funding. -Oversee and
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. -Supervise part-time student labor to accomplish the research project. -Assist with and contribute to various program managerial activities. -Perform other job related duties as required. Required Education
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communication skills. Ability to design experiments independently with limited assistance. Competency with laboratory work and use of analytical instrumentation. Proven track record of peer-reviewed publications
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records of results, as well as utilizing computer programs and databases to conduct analyses. -Perform experiments needed to evaluate the nutritional status of various engineered microbes for gene edited
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to participate in meetings with stakeholders/industry representatives. General Description: Assist with validating novel assays related to inflammation and energetics in skeletal muscle samples in an array
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from various institutions. Assist with writing grant proposals, manuscripts, and presentation of research results at academic symposiums/lab meetings. Train junior lab members. Required Education and
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: Expertise in interpreting LC-MS, GC-MS, Raman spectroscopy, and NMR data. Experience in metabolic profiling and quantification of bioactive compounds in plants. Familiarity with computational modeling