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USDA-ARS Molecular Biology Postdoctoral Fellowship in the Natural Products Utilization Research Unit
interactions. These directives require a multifaceted approach involving physiological, biochemical, and molecular experiments and the use of numerous techniques such as RNA-seq, data mining of DNA and protein
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mining Experience in one or more of the following is considered an advantage: network analysis, graph methods, knowledge representation or ontologies; mechanistic, causal or dynamic modelling of biological
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. Demonstrated expertise in sentiment analysis, opinion mining, or computational analysis of media and public discourse. Candidates should be able to connect computational analysis with communication theories and
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graph construction and mining, CDE development for data harmonization. Regulatory science and explainable AI, verification, validation, uncertainty quantification, and AI evaluation framework High
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. Apply the platform to large-scale transporter discovery by performing gene mining, constructing and screening transporter libraries, engineering microbial hosts, and analyzing pooled sequencing data
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uncertainty. Utilize machine-learning and data-mining approaches to recommend bioengineering interventions. Develop new machine-learning algorithms. Integrate machine learning techniques with mechanistic
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discovery by performing gene mining, constructing and screening transporter libraries, engineering microbial hosts, and analyzing pooled sequencing data to identify transporter function. Interpret and present
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School of Mechanical and Mining Engineering, Faculty of EAIT Full-time (100%), fixed-term position for up to 12 months Academic Level A or B (Postdoctoral Research Fellow / Research Fellow) Level A
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intricate. Specializing in program analysis and software analytics, the lab works on enhancing the precision and scalability of static analyses and mining insights from software repositories. Ongoing research
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and adoption of interventions that respond to changing needs of the region and its people around climate change, energy, mining, soil and water contamination, food production and livelihoods