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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 18 days ago
will develop computer vision, machine learning and control algorithms for a robot to perform packaging tasks. Human demonstrations will be used to generate data for learning. These data will encompass
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integrating modeling, machine learning (ML), and advanced control methodologies. The research will focus on designing AI-driven algorithms to assess battery health, predict degradation trends, and optimize
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research and innovation agenda by: Conduct applied or fundamental research and publish the results in high-quality conferences and journals; Developing Computational Intelligence (e.g., Machine Learning and
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. You are driven by scientific curiosity, enjoy working with complex multi-physics models, and are eager to advance probabilistic methods, machine learning tools, and simulation techniques. If you thrive
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learning video-AI models; b) assess representational alignment of bio-inspired deep learning models to the human brain. The bio-inspired models will be enriched with different temporal integration mechanisms
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inference, and Machine Learning methods. In addition to leading their own research projects, the appointed candidate will have the opportunity to contribute to the projects of PhD students in the group, as
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root architecture and soil characteristics. Nominate and help evaluate promoter regions and candidate genes to enhance nitrogen use efficiency. Apply machine learning models to classify molecular
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knowledge, incorporate reliability/uncertainty, and/or explainable models. The position is in the Digital Signal Processing and Image Analysis Group, Section for Machine Learning, Department of Informatics
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critical maritime operation or system Collecting and curating operational and security-related data for AI-based threat analysis Training AI and machine learning models for anomaly and threat detection
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hydro-climatic conditions govern vegetation behaviour, and how vegetation impairs the functioning of drainage and water-management assets. Using advanced geospatial modelling, machine learning and digital