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and pangenome scale analysis of fungal pathogens of agricultural crops. Anticipated Division of Time Lab and Computational Research: 40% Field and Greenhouse Research: 20% Writing, Data Analysis, and
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economics, data science or closely related field, with strong quantitative skills and demonstrated experience in applied econometric analysis, large-scale data integration, and global or regional economic
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members and be responsible for contributing to: Manuscripts, reports, abstracts for conferences, grant proposals Data analysis and pipeline development Technology-based solutions for advancing population
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dimensions of well-being beyond productivity) and identifying interactions across interventions. · Data analysis, with particular attention to the use of experimental and non-experimental approaches to causal
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library preparation, and analyze microbiome data. The candidate will also perform quantitative trait loci (QTL) analysis and is expected to summarize and present results both within the lab and at
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, particularly of non-model organisms Computer programming and experience with the solution of numerical problems, machine vision, and analysis of next-generation sequencing data High-throughput screening
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. The candidate will evaluate plant phenotypes, sample plant tissues, perform DNA extractions and metabarcoding library preparation, and analyze microbiome data. The candidate will also perform quantitative trait
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of impactful scientific publications Experience designing and carrying out synchrotron x-ray experiments Proficiency with scientific software for advanced data analysis and/or experimental control (e.g., Python
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(e.g., transcriptomics, proteomics, metabolomics) - Microscopy methods, FT-IR spectroscopy, or other analytical imaging techniques - Analysis of next-generation sequencing data - Programming skills (e.g
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-generation sequencing data Programming skills (e.g., Python, R) for data analysis, numerical modeling, or machine vision Supervision Exercised This position carries a high degree of independence