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flow behavior. The project also involves applying machine learning and computer vision techniques to enhance data analysis, pattern recognition, modeling, and prediction. The role requires a solid
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Biological Learning Machine, which is headed by Professor Jan Østergaard. The goal is to develop novel information-theoretic methods for identifying and analyzing temporal and spatial patterns of synergy and
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the Future 5G/6G Deployments with Millimeter Wave Integrated Circuit Interfaces Generated by Deep Computer Vision. This project is funded by FCT/MECI through national funds and when applicable co-funded EU
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to have a strong interest in data analysis, and medical research, along with relevant academic background and skills within medical image analysis and machine learning that will enable them to contribute
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enhance real-time decision-making in road traffic management. The project aims to bridge the gap between recent advances in AI and machine learning, in particular, multimodal and instruction-tuned
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south of Oslo. via Unsplash Main responsibilities Development and testing of digital solutions for small forest owners. These solutions include Computer vision models and a digital assistant based on a
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Learning, or related field Strong programming skills (Python, deep learning frameworks) Experience with computer vision and/or machine learning Excellent English communication skills (written and spoken
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Topics and bibliography Topic: Artificial Intelligence, Deep Learning, Computer Vision For further details, please contact us at the e-mail address vlad.hondru@fmi.unibuc.ro , contact person: Asist. Drd
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courses on advanced semiconductor technologies Design pathfinding PDKs as learning assets Interuniversity research programs across Europe 🔬 Nano IC-related PhD topics include: Machine-learning for epitaxy
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the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity