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willing and able to learn quickly within a collaborative and interdisciplinary team. Instructions on how to apply For more information and documents/templates/europass link, please visit https
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-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven models for complex data, including high
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collaborate with multiple stakeholders and conduct applied research in silviculture, forest ecology, pathology, policy and planning. We teach bachelor, Masters and PhD level courses addressing all
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proposal that will be further developed and contextualized in collaboration with the research leader in the research environment. Your research topic needs to be relevant for student learning in higher
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examined. You will be expected to participate actively in the department’s knowledge environment and networks, both internally and externally. The work is carried out in projects, and you will collaborate
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expertise. In addition, Uppsala University has a highly developed innovation office that gives support for commercialization and external collaboration. Read more here. Uppsala University offers one
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innovative methods for the scientific study of collaboration. Within the framework of RoC, a Community of Practice is also being developed - a common arena of knowledge and interest for shared learning and
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Description of the workplace The position is located at the division of Packaging Logistics at the Department of Design Sciences at LTH, Lund University in collaboration with the division
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bioinformatics methods have made significant strides, AI approaches - particularly deep learning - are revealing patterns and relationships in biological data that were previously inaccessible. As a postdoctoral
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applied machine learning projects in, e.g., computer vision, in close collaboration with industry partners. The position is not connected to an existing project, so the postdoc fellow will either join an