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) will be responsible for the design, analysis, interpretation, and presentation of experiments regarding the study of molecular mechanisms of the regulation of synaptic transmission in mammalian brain and
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of HEOR, including cost studies, data analytics, economic models, real-world evidence, services utilization analysis, systematic literature reviews, and patient-reported outcomes (PROs) research. The Fellow
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for analyzing behavioral and neural data (e.g. modeling behavior, time series analysis, statistical inference). Writing manuscripts to communicate project results, submitting to journals, and presenting
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The candidate should have skills and experiences in at least one of the following areas: 1) advanced characterization and modeling of pavement materials and mechanistic-empirical pavement analysis, 2) life-cycle
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materials and mechanistic-empirical pavement analysis, 2) life-cycle assessment of pavements of transportation infrastructure. The successful candidate is expected to be self-motivated and can think broadly
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-reviewed publications and presentations. Prior experience with DNA isolation from diverse environmental sample, Nanopore sequencing of DNA and data analysis is required. Certifications/Licenses Required
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, microbiology, or a related discipline, along with experience in polysaccharide extraction, structural analysis, and microbial cultivation. Experience with anaerobic microbiology and animal handling is a plus
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analysis, and microbial cultivation. Experience with anaerobic microbiology and animal handling is a plus, though not required. Knowledge of bioinformatics is highly advantageous, but not mandatory
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of this position are the following: Conducts research processes and procedures in the PI laboratory. Assists in the acquisition and analysis of data. Supports PI’s plans, developments, and implementations
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psychophysics and neuroimaging, or a related discipline. Certifications/Licenses Required Knowledge, Skills, and Abilities Training and/or experience with: Programming of behavioral experiments and data analysis