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discipline Academic excellence and research achievement Strong oral and written communication Ability to work in a team environment and high self-motivation Desired Qualifications Expertise in data analysis (R
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data analysis. Familiarity with flow cytometry software (e.g., FlowJo, FCS Express, R) and statistical tools for data analysis. Experience with high dimensional reduction and clustering pipelines
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. Candidate should have experience in sensor technology, irrigation, and agricultural field research. Excellent statistics practical knowledge. Familiarity with programming languages such as Python, R, and Java
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desirable. Preference will be given to applicants with in-depth data processing and statistical expertise (e.g., experience with R software, data aggregation, and multi-level mixed effects modeling). Required
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regression techniques. Strong quantitative and programming skills (e.g., R, Python, or MATLAB). Solid foundation in advanced mathematics, including topics such as real analysis, complex analysis, computational
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structural modeling and estimation. Advanced knowledge in causal inference and use of econometric tools and statistical software (e.g., Stata, R, Python) to conduct research using secondary and primary data