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on how to apply novel methodology. Deepen subject-matter knowledge through literature review and active engagement with current research developments. Work closely with academic advisors and collaborators
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explainable AI (XAI) methods with user-centred interaction design, combine machine learning with alternative AI methodologies (e.g., rule-based reasoning, knowledge graphs, hybrid approaches where relevant
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background, gender, sexual orientation, disability or age. We strive to create a safe and inclusive environment in which everyone can flourish and contribute. Knowledge security screening can be part of
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, and how AI systems can remain responsive to contextual knowledge in real decision environments. Another possible avenue concerns theorising with data, focusing on how inductive machine learning
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. The lack of knowledge is related to the models that should be used to auralize UAM in urban environments: new models are needed to predict noise exposure in urban cities. Traditional aircraft noise studies
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science, environmental modelling, geosciences, or related field with strong quantitative focus; Strong background in machine learning methods such as neural networks and transformers; Knowledge on handling
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challenging, and skills quickly become outdated due to fast-developing technologies (AI, XR, robots). Currently, most Smart Industry companies lack human capital and knowledge to achieve their maximum potential
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. Your work will generate knowledge and practical solutions that support public and private stakeholders in improving animal health, strengthening disease prevention, and advancing sustainable livestock
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methodological statistics You should have advanced programming skills in R or in other statistical software such as Python, or MATLAB. You should have a solid knowledge of statistical inference, statistical
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signal, e.g., labels of a downstream task, and background knowledge about the concepts. We also envision some practical applications of this framework in cross-species translation (transfer of findings