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Job Description Apply now Req Id: 32150 Job Title: Research Development Assistant City: West Lafayette Job Description: Job Summary Looking for an on-campus job where you can learn about higher
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of the Chair of the College’s AI Working Group, in coordination with the Associate Dean for Research, Graduate Programs, and Faculty Development on college-wide AI initiatives which may include: (1) Collaborate
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to: Designing and implementing pharmaceutical evaluation studies using RWD and/or omics data Extracting, cleaning, and processing large-scale EHR, claims and/or omics data for analysis Developing and applying
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The Quantum Semiconductor Systems Group under the direction of Prof. Michael Manfra seeks a scientist with expertise in semiconductor nanofabrication to support several projects related to the development and
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seeking a Postdoctoral Associate to join our dark matter group and work on the LZ experiment as well as the development of new detector technologies. LZ is a dual-phase liquid xenon time projection chamber
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on the development and evaluation of interventions to improve substance use and infectious disease outcomes. Work in the lab also incorporates implementation science approaches to improve substance use and infectious
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data. The appointed Post-Doctoral Research Associate will lead the development and administration of surveys, derive appropriate theoretical and empirical approaches for analyzing survey data, and assist
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nuclear and particle physics research leveraging machine learning and AI for data analysis and detector development, as well as exploratory work in quantum algorithms, depending on background and interests
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, to identify and characterize novel transcriptional regulatory mechanisms that control traits of agronomic importance. This project thus offers a unique opportunity to train a future leader in combining
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of different disciplines and include development of both technical and professional skills to ensure the most successful outcome for individual growth and career preparation. The Institute for Digital Forestry