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) from thawing permafrost. More specifically, the project focuses on the accumulation of Hg within the food web, with specific emphasis on transfer across classic ecosystem boundaries, from aquatic
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. The work involves areas such as AI-assisted automation engineering, digital twins, semantic modeling, secure data exchange, and reconfigurable production architectures. The research is carried out in
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semantic representation models for sign language. Such representations are key to allowing SL to be efficiently processed by large language models (LLMs), and will lead to machine learning models that can
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environments - Semantic scene-understanding in natural environments for robust decision-making - Learning-based traversability-aware path planning and safe trajectory generation - Resilient mission design for
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the possibility of extension. Starting at the earliest convenience. Application Submit the application via the University’s web-based recruitment tool, Varbi. Applicants are responsible for submitting a complete
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Box 118 22100 Lund Web Page: http://www.maths.lu.se/english/
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reports: Document no more than 10 pages each. For longer documents (eg dissertations), attach a summary (abstract) and a web link to the full text. One recommendation letter Contact information for two
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be made for special reasons). Experience in research on digital cultures. Proficiency in AI methods (e.g., NLP techniques, machine learning, and large language models, LLMs)—including web scraping
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Brändén Email: Postal Mail: Lindstedtsvägen 25 100 44 Stockholm Sweden Web Page: www.math.kth.se
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journals on data privacy (Transactions on Data Privacy), and has active links with the private and public sectors. For more information see https://www. umu.se/en/research/groups/nausica-privacy-aware