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finite element modeling programs such as SCIRun, COMSOL, or similar Special Instructions to Applicants: Applications should include a CV/resume, a brief (1 page maximum) statement of their career goals
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Data analysis experience, including AI and machine learning methods Interest in learning or experience with high performance computing Broad knowledge of college sports and/or elite-level competitive
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systems Proficiency in data analysis software and statistical methods Excellent written and verbal communication skills Ability to work independently while contributing to team goals Commitment to inclusive
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of machine learning methods for assurance on hardware devices like PCBs and ICs as well as on the development of automated hardware reverse engineering approaches at the IC and PCB levels for design recovery
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, mathematics or related majors Job Description: The Postdoctoral Researcher will play a key role in developing and applying cutting-edge AI methods to analyze large-scale clinical datasets, including electronic
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resistance, 2) assessing the role of phenotypic plasticity in its competitive success, and 3) developing robust methods for spectral phenotyping using ground, drone, and satellite-based sensors. This position
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disorders, Alzheimer’s disease, human genetics, transcriptomic analysis, epigenetic study, patient derived models, mouse models of neurodegenerative disorders, immuno-based methods, CRISPR/Cas based tools
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research team to contribute to projects at the intersection of AI/ML, real-world data, and health outcomes. The Postdoctoral Researcher will play a key role in developing and applying cutting-edge methods
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: The successful candidate will have demonstrated research experience with VR and/or eye-tracking technologies. Technical expertise in Artificial Intelligence. Strong quantitative, qualitative, or mixed-methods
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. Preferred: Expertise in Evo-Devo methods, genetics, genomics, molecular biology, neurophysiology, microscopy, and/or behavior methods. Demonstrated ability to critically think and work independently. Strong