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identification and prediction via software such as Python and R. Also, background in field design and statistical data analysis in the context of agriculture and applied plant pathology. Key responsibilities
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: Analyses Utilize statistical programming languages including but not limited Stata, SAS, R, Python. Perform data linkages. Perform statistical analysis of large dataset to investigate the associations
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project management position for defense or intelligence R&D programs with experience in technology assessment, systems design, system analysis, executing on multiple technical programs with scheduled
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analysis, with experience in languages and tools such as Python, IDL, MATLAB, C/C++, R, PyTorch, TensorFlow. For the Assistant Research Professor level, a proven track record of independent research and peer
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in climate, energy and sustainability issues. Background in quantitative analysis, data collection and management. Excellent writing skills. Coding skills in R and/or Python. Dedication and strong
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Production Perform R&D at a level comparable to Assistant Professor Expected to begin to apply as a PI for single-investigator proposals and to be co-PIs on larger proposals Demonstrate all the relevant skills
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to run their R&D programs, which will be consistent with the overall ARLIS mission. Exceptional candidates in all areas related to the ARLIS’s current research trajectories will be given serious
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. Expertise with common statistics and programming software (e.g., R, Python). Proficiency in using spatially resolved and georeferenced data. Strong capabilities in presenting analysis via written, visual and
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and statistical skills (e.g., such as Python, IDL, MatLab, C/C++, R, TensorFlow) are required. Candidates at the level of Assistant Research Professor must have a demonstrated ability to independently
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and quantitative skills; Basic knowledge of machine learning techniques; Proficient with Python and/or R programming languages Excellent English oral, written, and interpersonal communication skills