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machine elements. In the undergraduate program, the main two programs focusing on the international profile of the Division of Materials Science are important for the department, namely the EEIGM master's
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out together with seven industrial partners and is externally funded by the Knowledge Foundation. In co-production with our corporate partners and the community, we develop concepts, principles, methods
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at Uppsala University? Find out more about what it´s like to work and live in Sweden. Where to apply Website https://uu.varbi.com/en/what:job/jobID:968823/type:job/where:39/apply:1 Requirements Research
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tissue formation, and limited spatial precision. Building on our recent advances in enzyme-triggered electrode fabrication in living systems (Strakosas et al., Science, 2023, https://doi.org/10.1126
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qualitative and/or quantitative research methods. Experience with surveys, interviews, and/or statistical analysis. Proficiency in written and oral communication in English. Experience of collaboration with
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strategies studied in comparison with conventional remediation strategies. The project aims to develop and apply methods for assessing environmental impact, ecosystem services, and technical and socioeconomic
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(email address and telephone number), and 7) any publications. You are welcome to submit your application no later than 2 November 2026.UFV-PA 2026/2671. Where to apply Website https://uu.varbi.com/en
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Institute of Neuroscience and physiology, Sahlgrenska Academy, university of Gothenburg | Sweden | 21 days ago
University of Gothenburg can be found on the university's doctoral student pages. https://www.gu.se/en/doctoral-studies Duties The PhD education in Medical Science comprises carrying out a scientific project
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tissue-based profiling methods such as gene expression analysis, DNA sequencing, single-cell sequencing, and spatial transcriptomics. These high-dimensional data are analyzed using advanced bioinformatic
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Join MultiD Analyses AB and the University of Gothenburg to develop innovative bioinformatics and machine learning methods for RNA Fragmentomics, with the ambition to improve cancer care through