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for a: PhD Candidate in Emotionally and Socially Aware Natural Language Processing (1.0fte) Project description Current Natural Language Processing (NLP) systems, and especially large language models
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the training of these systems, is treated mainly as data rather than as a social practice shaped by people, culture, and context. This PhD project investigates how to make NLP systems emotionally and socially
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because language, in the training of these systems, is treated mainly as data rather than as a social practice shaped by people, culture, and context. This PhD project investigates how to make NLP systems
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software engineering, computer science, data science, bioengineering, bioinformatics, engineering, physics or related Experience in either machine learning or computational biology. Interest in both
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software engineering, computer science, data science, bioengineering, bioinformatics, engineering, physics or related Experience in either machine learning or computational biology. Interest in both
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on the monitoring and response parts, building on many earlier projects revolving around the use of UAV/drones, computer vision and machine learning, change and damage detection, and multi-data integration, such as
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correction. This machine-learning approach, however, needs a realistic model of light propagation in the retina in order to validate it and to generate the large volumes of training data required. Funding
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processing and machine learning methods, and big data analytics solutions to extract highly accurate large-scale geo-information from big Earth observation data. Our team aims at tackling societal grand
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-physical system Sensor fusion, perception and big data Cybersecurity, automotive networking Simulations, verifications and validations of autonomous vehicles Human-machine interfaces and interactions Self
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, perception and big data Cybersecurity, automotive networking Simulations, verifications and validations of autonomous vehicles Human-machine interfaces and interactions Self-driving shuttle bus deployment and