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Grant(s) (RG) in the scope of R&D projects FireLSF - Development of predictive models for the fire resistance of light steel frame walls - an integrated experimental, numerical and machine learning
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manage large-scale materials datasets. • Develop GNN architectures for predicting materials properties from atomic graphs. • Train and deploy machine-learned force fields for MD simulations and rapid
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Systems Monitors and coordinates use of computerized integrated learning system, and student computers Uses state DOC computer system to set up class schedules; coordinates and resolves student conflicts
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authorization To apply, visit https://jobs.uci.edu/careers-home/jobs/109783 Copyright 2025 Jobelephant.com Inc. All rights reserved. Posted by the FREE value-added recruitment advertising agency jeid
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delivery of effective, compassionate and accessible care informed by research within correctional environments. We Care. We Teach. We Heal. We Improve. Posting Summary Rutgers University Correctional Health
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University of Maryland, Baltimore County | Southern Md Facility, Maryland | United States | 2 days ago
Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 09-Jan-26 Location: MD Type: Full-time Categories: Academic/Faculty Computer/Information Sciences Internal Number
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
from This Employer https://main.hercjobs.org/jobs/21955832/post-doc-research-associate Return to Search Results
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at Dana-Farber Cancer Institute More Jobs from This Employer https://main.hercjobs.org/jobs/21940222/nurse-practitioner-physician-assistant-assistant-cancer-hematology Return to Search Results
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. Connections working at Dana-Farber Cancer Institute More Jobs from This Employer https://main.hercjobs.org/jobs/21940282/nurse-practitioner-physician-assistant-palliative-care Return to Search Results
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Intelligence & Machine Learning Engineer/Scientist I works within the Artificial Intelligence Operations and Data Science Services group (AIOS) in the Informatics & Analytics department of Dana-Farber Cancer