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consequences, and assess the effectiveness of the adopted mitigation measures. Model-Based Safety Analysis (MBSA) is listed as an acceptable and recommended means of compliance to perform safety assessment in
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research problem in its own right, advancing both the conceptual foundations and computational tools for assessing NLP systems in ways that are reliable, valid, and human-centred. Application domains include
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. The research will integrate external knowledge and computational argumentation to produce reliable, persuasive, and ethically grounded responses, while also addressing the moral values and motivations of users
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introduce processing artifacts, creating a direct barrier to robust and reliable AI classification. AI4IV’s mission is to address these limitations and become a leader in AI for vision by providing
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and bandwidth usage; iii) investigating how explainability and robustness can be maintained in compressed models deployed at the far edge, ensuring trustworthiness and reliability in real-world
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and simulation techniques are necessary to develop Urban Digital Twins able to manage this complexity and produce reliable predictions. The candidate will be requested to contribute to this research
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with familiarity with foundation models (e.g. vision language models) and the ability to design and prototype innovative, reliable and reproducible solutions for complex 3D scene understanding tasks
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, and the integration of compliance requirements into decision-making structures. It will combine doctrinal legal analysis with case studies and design-oriented methodologies in order to develop
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, and a Continuum+K3 GIF. The group will also further data analysis using and developing software routines for analysis of large datasets. Research projects span beam-sensitive materials with
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analysis and developing advanced data interpretation methods, SPACE-MEL aims to unlock deeper insights into cellular organisation and disease mechanisms. The network will train 15 Doctoral Candidates through