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Field
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, and marker development. Experiences to analyze high through put data sets including short- and long-read genomic and transcriptomic data, and develop or apply related software for data mining. Familiar
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decision-making, and collective action. The Postdoctoral Fellow will help extract relevant open-source information in a guided snowball data collection manner by leveraging cyber forensics and deep web
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, and collective action. The Postdoctoral Fellow will help extract relevant open-source information in a guided snowball data collection manner by leveraging cyber forensics and deep web search-based
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NetworkX, igraph, and Gephi for complex network and graph-based data exploration; Foundational understanding of computational social science and social network analysis; Expertise in social media mining and
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decision-making, and collective action. The Postdoctoral Fellow will help extract relevant open-source information in a guided snowball data collection manner by leveraging cyber forensics and deep web
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study characterizing translation functions across human 5′ UTRs (Lewis et al., Molecular Cell, 2025. PMID: 39706187). Responsibilities will include computational mining of viral metagenomic databases
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conditions. Bioinformatics skills relevant to genomics-driven natural products discovery, including genome mining, biosynthetic gene cluster analysis, sequence alignment, and annotation. Strong quantitative
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environment where your work contributes to shaping sustainable mining practices globally. As part of the Centre for Environmental Responsibility in Mining (CERM), you will work alongside an interdisciplinary
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USDA-ARS Molecular Biology Postdoctoral Fellowship in the Natural Products Utilization Research Unit
involving physiological, biochemical, and molecular experiments and the use of numerous techniques such as RNA-seq, data mining of DNA and protein sequence databases, analysis of gene function via CRISPR/Cas
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preparation, and proposal preparation; (e) have strong statistical knowledge and data analysis skills; (f) be proficient in using Python for data processing and text mining, and traditional qualitative