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highly interdisciplinary project Interest in the topics of one of the two projects Bonus: Experience working with social media data, mental health, social networks, natural language processing, experiment
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interconnected research pillars drive innovation: Sustainable Natural Resource Utilization Microbial and Enzymatic Conversion Process Circularity Your personal sphere of play: We are excited to announce a
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developing and applying deep learning models, particularly in areas such as natural language processing (e.g. use of LLMs), computer vision (e.g. CNNs for image classification), and multimodal data integration
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successful candidate will possess skills in natural language processing and deep learning. Experience of studying the robustness and generalisability of LLM would be beneficial. This is a full time post (35
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(generative models, real-time dashboards). Data analysis and geospatial tools (QGIS, ArcGIS, remote sensing). Visualization and communication tools (Adobe Creative Suite, Blender). Language & other skills
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Project The Adaptive Design for AI-Driven Processes in Transforming Dynamic Landscapes (ADAPT) project develops scalable, data-driven design methodologies that transform dynamic environmental processes
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applications (e.g. natural language processing, multivariate time-series data), to develop systems that improve the efficacy of machine learning-based technologies for healthcare applications. You must hold a
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into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and applications (e.g. natural language processing, multivariate time-series data
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should have experience of working with computational and analytical techniques in the areas of natural language processing (including, among others, topic modelling), computational linguistics, and machine
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for candidates to have the following skills and experience: Essential criteria PhD or equivalent experience in relevant area. Knowledge or interest in Natural Language Processing, ideally as applied to big