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to reconstruct subsurface defects; Implement image/signal‑processing or machine‑learning pipelines for automated flaw characterisation; Collaborate with the Federal University of Rio de Janeiro, including short
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, multimodal imaging, and AI-assisted diagnostics to enable safer and more effective screening and therapy. The postholder will focus on developing and applying advanced computer vision and machine learning
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for cognitive science and artificial intelligence, including about 35 PhD students. Core research domains include cognitive science, machine learning, deep learning, games, virtual reality, computational
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focused on the challenge of accelerating ternary neural networks using FPGA devices. The successful candidate will have significant experience in machine learning, FPGA design and an outstanding track
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models and machine learning techniques for kinetic equations arising from plasma and neutron transport. The position will be based at Virginia Tech’s campus in Blacksburg, VA. The postdoc will have a
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ternary neural networks using FPGA devices. The successful candidate will have significant experience in machine learning, FPGA design and an outstanding track record in conducting machine learning research
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develop statistical and machine learning models to identify and validate predictive biomarkers of resistance evolution in Pseudomonas aeruginosa lung infection. As part of this work, the postholder will
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, high-performance computing (HPC), dimensionality reduction, and machine learning. Your responsibilities will include publishing research in leading conferences and journals, contributing to grant
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results in leading conferences and journals Required Qualifications PhD in one of the following areas (or related fields): Machine learning / deep learning Quantum computing / quantum information Applied
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preferably start around 01-12-2025 and requires knowledge of geometric image processing and machine learning. Information As Post-doctoral Researcher within VICI Project "Geometric Learning for Image Analysis