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for coupling functional genomics techniques with computational analyses to understand gene regulation in health and disease. Such models are based on multi-omics high-throughput assays, either performed by
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in special areas of interest to the overall research program of the laboratory. Performs highly skilled on experiments and data analysis to dissect transcriptomic, metabolomic, proteomic changes in rat
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-scale energy models to analyze high-performance buildings and geothermal energy systems. (3) Assess technical and non-technical barriers to the adoption of clean energy technologies. (4) Conduct analyses
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, circuit, and computational approaches to examine neural activity in awake-behaving rodents performing auditory and audiovisual tasks. These approaches include high-channel count silicon-probe
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group led by Dr. David Klinges in the Department of Ecology, Evolution & Natural Resources. Our work combines computational modeling, field studies, and laboratory experiments to understand how
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of planetary atmospheres and surface environments · Strong programming skills (e.g., Python, C/C++, or Fortran) and familiarity with high-performance computing, and · Excellent organizational and written and
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high proficiency in R and/or other computer programming languages. Applicants in All But Degree Status will be considered for interviews. Preferred Qualifications Experience with computational
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Investigator. The Postdoctoral Associate performs research, experiments, and laboratory techniques of a specialized nature under direct supervision of the Principal Investigator and drafts written reports
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a strong computational background and extensive experience developing high-throughput systems for quantitative analysis of behavior and aging, allowing us to connect neural and molecular mechanisms
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decline. The laboratory also has a strong computational background and extensive experience developing high-throughput systems for quantitative analysis of behavior and aging, allowing us to connect neural