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learning algorithms, and elucidating structure-property relationships of emerging molecules, polymers, solid-state materials, formulations, etc. Tasks include: Managing the research and development projects
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About the Opportunity Job Summary: The Open6G group at the Institute for the Intelligent Networked Systems (INSI), Northeastern University, is leading research and development, testing and
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, to create a unified and reliable representation of structural integrity. The work expands on TU/e’s contributions by developing algorithmic components for detection and classification of defects and anomalies
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, including experimental design and reinforcement learning algorithms. We combine statistical methods with online reinforcement learning algorithms to develop reinforcement learning algorithms and inferential
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 22 days ago
research, development, and innovation centre active in the fields of High-Performance Computing (HPC), Data Analytics (HPDA), Artificial Intelligence (AI), and Quantum Computing (QC) and their applications
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Discovery”, with a strong scientific and environmental ambition: developing lower-footprint AI methods for real inverse problems in nondestructive evaluation. The topic has already passed the first ENACT
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Transparency). The main tasks will be to: Develop AI-assisted tools leveraging large language models (LLMs) to support community-based fact-checking Designi and evaluate methods to improve the robustness
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in the Phi_Lab, led by Dr. Azeem Ahmad, and will focus on the development of advanced reconstruction algorithms and next-generation quantitative optical microscopy and tomography systems for imaging
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Posting Details Student Title Classification Information Quick Link https://chapman.peopleadmin.com/postings/39061 Job Number SE176424 Position Information Department or Unit Name Fowler School
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University. This research opportunity will be focused primarily on the development and application of novel computational algorithms to analyze and integrate diverse omics datasets, including bulk and single