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teaching and learning. The purpose of the position is to develop the independence as a researcher and to create the opportunity of further development. Your primary focus will be on conducting high-impact
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microorganisms, and developing of spectral collection and analysis protocols that will allow this biochemical data to be effectively used to support optical microscopy-based deep-learning algorithms for species
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facility belonging to SciLifeLab, part of a national infrastructure for research in life science. The creative and research-intense environment contributes to a broad knowledge-base as well as cutting-edge
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education and to the educational programmes at MDU. A broad range of topics and perspectives are thereby possible (workplace-based learning, simulation in professional education, student characteristics etc
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to solving applied problems through research, collaboration and education on sustainable plant production. We teach and research plants for food, feed and energy. The research and teaching focus
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classification and multi-layered environment mapping -Digital twin generation for natural environments -Semantic scene-understanding in natural environments for robust decision-making -Learning-based
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great advantage: Forest and wood production processes Wood construction Furniture manufacturing Wood material science Machine learning Process simulation and optimisation The postdoctoral fellow is part
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-assembly mechanisms, identifying robust experimental signatures of collective properties, exploring practical applications, and utilizing artificial intelligence and machine learning to aid in this process
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candidate will be a key member of the DarkTree project, funded by the Knut and Alice Wallenberg Foundation. The project aims to fill the gaps in the genome-based insect tree of life using the unique global
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bioinformatics, with a particular emphasis on performing analysis of high-dimensional data, which can be sequencing and/or imaging-based. Experience working with AI and machine learning approaches are considered a