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. More information about the department is available at: https://www.umu.se/en/department-of-computing-science/ Is this interesting for you? We welcome your application until August 1, 2025. Project
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environment project, we will develop automated species and community recognition, particularly focusing on pathogenic soil fungi, with help of deep-learning algorithms fed with microscopic image and Raman
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, Carbon, Small, and IEEE Electron Device Letters and IEEE Transactions on Component Packaging and Manufacturing Technology. About the research project We aim to develop a completely new 2D hexagonal boron
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Biophysics) at Karolinska Institutet, Stockholm, Sweden). Your mission This interdisciplinary project leverages expertise in mitochondrial disease and molecular immunology to investigate the mechanisms and
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participating in projects that collect and utilize agronomic data from forages and crop rotations, and (3) writing scientific publications and grant applications. Qualifications: Required: A PhD degree in a
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: Structural integrity of materials is of primary concern in sustainable mechanical design, as more durable products impose longer product lives and allow the usage of less material. Accounting for structural
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? If so, this postdoctoral position is your opportunity to make an impact while working in a collaborative research group focused on cutting-edge battery materials and manufacturing. Project description
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this project is to investigate how turnout to pasture affects milk production and composition, blood metabolites, efficiency of nitrogen utilization, and behaviour of Nordic dairy cows. The second objective is
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of managing reverse logistics for returned products, and the potential disruptions to existing distribution networks. About us and the research project The division of Supply & Operations Management (SOM
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participation in other ongoing projects in the lab and clear communication of research findings to both specialized and general audiences are expected. Additional responsibilities include: performing data quality