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the EAA and ensuring equal participation in society. The ideal candidate will have a strong interest in accessibility, design methods, human-computer interaction, artificial intelligence, and human-centered
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to simulate cascading disaster effects, as well as satellite and sensor data, looking specifically at 6 different use cases across Europe. In addition to the detailed innovative analysis of existing methods and
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the PhD program in Computer Science and Computer Engineering with specialisation in Information Systems (IS). In the context of Prof. Fridgen's PayPal-FNR PEARL Research Grant and in strong synergy and
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Computer Engineering, Faculty of Science and Technology, University of Coimbra. This international tender shall be conducted pursuant to paragraph 1 of Article 57 of the Lei Geral do Trabalho em Funções
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Physiological Oxygen Levels for Enhanced Biomarker Discovery and Antioxidant Screening Beyond the Conventional Methods, with the number 16992 - Operation Code: COMPETE2030-FEDER-00828000, programme and tender
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description This project focuses on developing, analyzing and using probabilistic methods for dynamic phenomena evolving over space and time based on measurements from different and complementary sources. We
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research in information and digital technologies (computer science, automation, robotics, artificial intelligence), with the aim of developing methods for representation, analysis, and control of complex
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contribute to improved animal welfare, reduced antibiotic use, and a more sustainable pig production. The PhD candidate will play a central role in the project, from laboratory method development to field
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mathematical methods, algorithms, and applications are required. Simulators are a recognized method for architectural design explorations and the implementation of software development platforms. The goal
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap