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Field
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Scholarship code: SRS-25030 These prestigious La Trobe University scholarships (2), in partnership with the Australian Office of National Intelligence, will be awarded to outstanding applicants
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technologies represent a convenient opportunity to automate complex code analyses and transformation to obtain improved characteristics in the output code. Modern initiatives rely on a multi-layer approach to
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, healthcare and finance. Yet, while AI has demonstrated a high impact on applications on text and images, proportional progress on tabular data is lacking. With the TRL Lab (Table Representation Learning Lab
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organizations and typically informs important decisions in healthcare, governments and finance. Yet, while AI has demonstrated a high impact on applications on text and images, proportional progress on structured
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dialect speaker’, experiences of encountering other language and cultural codes and norms in relation to migration from rural to urban areas, or shifting attitudes toward dialect speakers over time. It is
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environment. Visible homelessness, such as encampments, is frequently seen as detrimental to cities’ public image. In response, public authorities are increasingly introducing laws and regulations
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seen as detrimental to cities’ public image. In response, public authorities are increasingly introducing laws and regulations that criminalise homelessness, prohibiting behaviours that homeless
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more (for an overview of these technologies, see http://behaverse.org/ ). Your role in this team will be to develop computational models and data analysis code to process large, multimodal behavioral
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of different expressive forms such as spoken or written language, (moving) images, animations, sound, gestures, or others. How do these expressive forms or semiotic modes interact to construct meaning? Which
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on argumentation as communicated through multimodal means, i.e. by the interplay of different expressive forms such as spoken or written language, (moving) images, animations, sound, gestures, or others. How do