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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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, machine learning, and bioinformatics tools. Expertise in CRISPR-based assays, especially CRISPR screening, is highly meriting, as is experience with single-cell RNA sequencing or other omics assays
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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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and Data Science for Spatial Genomics in Diabetes This position centers on the development and application of machine learning, image analysis, and integrative omics approaches to spatial
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fluids, flow-induced pattern formation in both simple and complex flows (e.g. flow instabilities, product defects), multiscale analysis, and the application of machine learning techniques. About the
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application! Work assignments Subject area: Computational studies of the influence of microstructural features on the structural integrity of metallic materials using machine learning Subject area description
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-scale computational methods, and bioinformatics. The division is also expanding in the area of data science and machine learning. Our department continuously strives to be an attractive employer. Equality
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high level of motivation and commitment, good aptitude/skills towards laboratory work and the willingness to learn. The applicant must also be organized, rigorous and be able to work both independently
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in labour unions, etc. We seek a talented and open-minded candidate, who is eager to learn and has a genuine scientific interest. Extensive knowledge in and practical experience with protein expression
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for the interview presentation. The interviews are performed by a panel of UCMR and UPSC researchers. The date of the final interview is 6-7 October 2025. Learn more about life as an ‘EC’ postdoc