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undergraduate and graduate trainees as appropriate in the lab and field. This position will be funded by USDA NIFA Agricultural Microbiome Program. The individual will need to have the ability to drive to field
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Dissemination: 20% Training, Supervision, and Program Support: 20% Requirements Required Qualifications: A PhD in plant pathology, plant biology, or a closely related discipline. Experience working with plant
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-LHC detector upgrades. The successful candidate is expected to engage actively in CMS measurements as well as the smart pixels program (https://fastmachinelearning.org/smart-pixels/ ). A PhD in
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research articles and present results at scientific meetings. (30%) • Assist in the development of proposals for external funding for research projects. (5%) Requirements • A PhD degree in physics, chemistry
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] Subject Areas: Physics / Hard Condensed Matter Theory , Machine Learning , Material Science , Physics , Quantum Information Science , Soft Condensed Matter Theory , theoretical condensed matter physics
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for dissolved organic matter. ● Integrate sensor outputs into process control systems (stepper motor–driven coagulant dosing). Desired qualifications: ● PhD in Environmental Engineering, Electrical/Computer
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, how long have you worked with the machine, and for what purposes/projects, · PhD degree in Computer Science, Electrical Engineering, Information Science, Mechanical Engineering, Human-Computer
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% Computer research 15% Field Research 7% Writing 15% Requirements Required: - PhD in Plant Biology, Microbiology, Entomology, Plant Pathology, or a related field. - Experience working with plants as part of