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in cortical circuits mediating defensive responding. Responsibilities will include rodent colony management, stereotaxic surgery, behavior testing, fiber photometry protocols and data analysis, brain
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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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and computation, involving the analysis of feedback controllers in systems and synthetic biology, the analysis of algorithms, and merging of ML and mechanistic approaches to deal with context effects
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combining artificial intelligence with human expertise. The lab develops knowledge-grounded artificial intelligence, text mining and knowledge assembly, mathematical and systems modeling, and causal analysis
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and data science. This cycle's focus is on AI-powered data analysis to advance hypothesis-driven research related to addiction. Computational analysis of previously collected data can increase the speed
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-powered data analysis to advance hypothesis-driven research related to addiction. Computational analysis of previously collected data can increase the speed and efficiency of life sciences research
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. Work will emphasize the development and analysis of advanced methods in areas such as sparse signal recovery, compressed sensing, and statistical estimation, with a particular focus on their role in
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energy-conversion testbeds, evaluating activity, selectivity, stability, and energy efficiency under realistic operating conditions Develop reaction and reactor models and conduct process analysis
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, data analysis/interpretation, and presentation of results Ability to work effectively in a highly integrated team environment Highly collaborative, self-motivated, and team-oriented individual Excellent
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field. Strong candidates will have a track record of research in peptide quantification and analysis (LC-MS/MS, HPLC, or equivalent), experience studying peptide-immune cell interactions, microbiome