465 machine-learning-"https:" "https:" "https:" "https:" Postdoctoral positions in United States
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: 281113699 Postdoctoral Research Associate D-25-ECE-00003 | Research | Electrical and Computer Engineering The Department of Electrical and Computer Engineering invites applications for postdoctoral, or more
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in computational methods, particularly those with backgrounds in machine learning, artificial intelligence (AI), statistics, bioinformatics, or analysis-acceleration technologies. Candidates should
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terminal degree with deep knowledge of Artificial Intelligence and Machine Learning. Desired Qualifications Ability to help create scalable Artificial Intelligence workflows. Experience in working with
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Monitoring Drift Chambers (MDT), and in the Event Filter track trigger (EFTracking). The group applies novel Machine Learning tools and techniques to both analyses and trigger upgrades, and leverages FPGA and
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virtual reality development, machine learning, or advanced data analyses and modeling are highly desirable. Position Status Full Time Posting Number 25FA0682 Posting Open Date Posting Close Date
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Remote Sensing; Machine Learning Models for Predicting Wildfire Spread; Wildfire Risk Assessment Through Multi-Modal Data Integration; Automated Vegetation and Fuel Load Mapping Using Computer Vision; AI
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subsea digital twin of deep-water mooring lines for floating offshore wind turbines. The digital twin will be integrated with machine learning algorithms for detection of primary entanglement due
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will continue to build from our learnings. https://pubs.rsc.org/en/content/articlelanding/2025/gc/d5gc01813g https://pubs.rsc.org/en/content/articlehtml/2018/gc/c7gc03747c https://pubs.rsc.org/en/content
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so classified. JOB SUMMARY We seek to hire a post-doctoral research associate with a background in organizational behavior, human-computer interaction, psychology, computer science or related
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for soft materials, with particular emphasis on thermo–visco–hyperelastic behavior, integrating continuum mechanics, scientific machine learning (SciML), and computational physics. The project aims