44 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Univ" positions at Umeå University
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development, networking, administrative and technical support functions, along with good employment conditions. More information about the department is available at: https://www.umu.se/en/department
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and tissue culture. Molecular biology and immunohistochemistry. Image analysis, data visualization, or programming. The position is full-time and limited to 6 months. Application Your application should
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datasets from Fennoscandian lakes—including climate data, water chemistry, biotic indicators, and satellite remote sensing. The main goal is to identify critical ecological thresholds that, when not met
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semesters (6 years), with programme starts each autumn and spring semester. More information about the programme can be found on the faculty web site - Doctoral studies at the Faculty of Medicine . About the
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preparation of samples for high-throughput sequencing. Proven experience coordinating and processing large numbers of environmental samples, with strong attention to quality control, documentation, and data
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. The project employs several techniques including fluorescence microscopy, electron microscopy, and advanced image data analysis. Duties Establishment of plasma membrane model systems and studies of replication
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with us, you receive the benefits of support in career development, networking, administrative and technical support functions, along with good employment conditions. More information about the
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anaerobic culturing techniques (e.g. anaerobic chamber, bioreactor) and analysis of 16S sequencing data. Furthermore, practical experience in working with mouse models is required. Other requirements
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two pages) 2. CV 3. Diplomas of bachelor and Master level degrees 4. Bachelor/Master theses work/other relevant publications 5. Other merits of relevance for the position 6. Contact information to two
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in radiotherapy with the goal of enabling fully adaptive radiotherapy. The work is based on deep learning, where models are trained on generated or clinical data. The project is carried out in