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Requisition Id 17180 Overview: We are seeking a Computational Physicist to carry out modeling of plasma transport and plasma-material interactions (PMI) in the Materials Plasma Exposure eXperiment
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at the intersection of applied mathematics, computational science, and high-performance computing. The successful candidate will help develop advanced scientific computing methods and deploy them on state-of-the-art
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. -Ensures program has sufficient and efficient computing capabilities (high performance research computing, workstations, software, network attached storage). -Oversees drone activities (including drone
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, support faculty in grant writing, and mentor data scientists, PhD students and undergraduate and graduate interns. Key Responsibilities : Perform independent research: own a research project from
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availability, and internal equity. Pay Range: $80,000 to $90,000 We invite applications for a Postdoctoral Research Associate to join a collaborative experiment–theory program investigating electron–ion
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of reproducible bioinformatics pipelines using workflow-management and containerization tools, or high-performance or cloud computing for large genomic datasets. Experience with single-cell RNA-seq analysis using
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pipelines Develop computational methods for the behavioral and psychological characterization of AI systems, including standardized assessments and behavioral experiments Leverage multimodal AI technologies
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innovative deposition processes and high-throughput materials screening. The opportunity Contribute to groundbreaking research on accelerated thin-film and process development for emerging applications such as
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leading role in detector operations and in major upgrade efforts, including the ITk Pixel detector and TDAQ systems. The group is also actively advancing work in high-performance computing (HPC) and machine
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develop and optimize scientific and engineering applications leveraging high-speed network capability provided by the Energy Sciences Network or run on next-generation high performance computing and data