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classification for conducting cutting-edge and life-changing research that creates impact in our communities. Additionally, for more than a decade, they have received a national Military Friendly® School
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- and machine-learning-based methods that automatically describe and model geodata sources using textual metadata (NLP) and the geodata itself; contribute to a corpus of geo-analytical scenarios with
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to the development of novel indoor localization and tracking methods, algorithms, and systems ? Evaluating the performance of such methods, algorithms, and systems via modeling and simulation ? Performance evaluation
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. This role involves supporting budgeting, forecasting, and financial reporting, analyzing data for trends, creating models for decision-making, and partnering with stakeholders to provide financial insights
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competitive ERC. The project focuses on the development of a first-principles, machine-learning-accelerated computational framework for modelling polymorphism, anharmonicity, and electron–phonon interactions in
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provides an accessible, quality education through flexible learning and unparalleled internship opportunities. At UA Little Rock, we prepare our more than 8,900 students to be innovators and responsible
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technical specifications. Knowledge, Skills, and Abilities: Advanced applied statistics skills, such as distributions, statistical testing, regression, etc. Professional experience developing machine learning
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image analysis packages such as Freesurfer, FSL, SPM, or 3DSlicer, or using machine learning or artificial intelligence models would be advantageous What We Offer The appointee would be exposed to ample
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in Spatial Omics and Multi-Modal Data Integration Duties & Responsibilities: Develop computational and machine learning methods for spatial omics data (spatial transcriptomics, spatial proteomics
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biological environments - Experience using machine‑learning algorithms for luminescence signal analysis and sensing applications - Experience writing scientific articles and presenting results at conferences