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distribution systems. Current research initiatives include developing advanced vibration analysis methodologies for wooden packaging systems, predictive modeling for packaging performance, and optimization
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through peer-reviewed publications and/or preprints • Ability to work independently as well as collaboratively Preferred Qualifications • Experience using Drosophila (fruit flies) as a research model
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• Ability to work independently as well as collaboratively Preferred Qualifications • Experience using Drosophila (fruit flies) as a research model • Experience in molecular biology techniques • Experience in
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or Immunology. The successful candidate will work on an interdisciplinary research project focused on murine models of brain injury and innate immune regulation. Qualified candidates will be expected to work in a
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or Immunology. The successful candidate will work on an interdisciplinary research project focused on murine models of brain injury and innate immune regulation. Qualified candidates will be expected to work in a
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’ projects. Our lab focuses on assessment and delivery of analgesic therapeutics in large animal models, from benchtop experiments to clinical research. Specifically, we work with pigs, dogs, cats, and
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surgeries, including transverse aortic constriction (TAC), myocardial infarction (MI), ischemia-reperfusion injury, and related surgical models of cardiovascular disease. The individual will also assist with
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technologies: ForceDecks, NordBord, ForceFrame - Data visualization tools: Tableau, Power BI - Data analysis & coding tools: R, Python - Machine Learning: Predictive modeling, feature engineering, model
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or Immunology. The successful candidate will work on an interdisciplinary research project focused on murine models of brain injury and innate immune regulation. Qualified candidates will be expected to work in a
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-Demonstrated experience with AI, machine learning and/or large language model (LLM) applications -Coursework or experience using data in an academic research setting Overtime Status Exempt: Not eligible