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techniques such as SEM, TEM, XRD, EDS, EBSD, FIB/SEM etc., as well as physico-mechanical characterization techniques such as tensile, compression, DSC/TGA, etc. as well as analysis of the data with good
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documented experience in computer vision, where the PhD project was fully or substantially method-focused on computer vision and/or AI-based image or video analysis have very strong knowledge of machine
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relevant medical science. Strong skills in data management and the ability to work with large datasets. Strong statistical analysis skills. Strong programming skills in a relevant statistical software
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comprehensive support for large‑scale multi‑omic data generation/analysis and transformation/embryogenesis services for functional validation. Nathaniel is also an associate group leader at the Science for Life
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techniques such as tensile, compression, DSC/TGA, etc. as well as analysis of the data with good knowledge of possible errors. hands-on experience with alloy design strategies, including high-throughput
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We are seeking a postdoctoral researcher with a background in the analysis of longitudinal health data. You should have substantial experience in structuring datasets from multiple sources to enable
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primary responsibility will be to carry out data collection and analysis in close collaboration with the researchers on the project. You key responsibilities include: Co-lead longitudinal data collection
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. Expertise in any of the following can be an advantage, but none is obligatory: Reproducible data analysis in R/Python/Julia Cell wall biochemistry Plant in vitro culture work In situ microscopy and
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science/ecology, especially related to agriculture. Computer programming. Data analysis (machine learning, statistics, numerical analysis, time-series analysis, etc.). Crop modeling. Quantitiative methods
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. For more information see www.ftf.lth.se , www.nano.lu.se , Work duties The focus of the project is analysis of fluorescence microscopy images of nanostructured surfaces in the context of single-molecule