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using Cell Painting and high-content imaging. Deep learning and multivariate methods, both supervised and unsupervised. Development of software and pipelines for analysis of large-scale image data
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chloroplasts. This project will develop and apply new synthetic biology methods with the aim to enhance the rate of carbon fixation and conversion in cyanobacteria. Such methods include, for example, CRISPR/Cas
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boundaries creates synergies that drive research forward and the high-tech methods enable research that would otherwise not be possible in Sweden. At SciLifeLab, we do not only apply the latest and most
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and includes both basic studies on disease causes and the development and evaluation of improved diagnostics and new treatment methods. More about the department’s activities can be found
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application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. Your tasks will include conducting independent research in the subject area at
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data as well as other modalities (i.e. microbiome) generated using the Spatial metaTranscriptomics (SmT) method. In addition, the PhD student will also apply Spatial Transcriptomics and single-cell
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sequencing platforms (e.g. NextSeq 2000, NovaSeq X Plus). The role also includes continuous improvement and standardization of existing analysis methods (e.g. single-cell applications, basic histology and
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General description of the DDLS Fellows programme Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels
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haplogroups, principal component analysis, analysis, analysis of kinship, trait analysis and metagenomic analysis (incl. analysis of pathogenic microorganisms). The bioinformatician is involved in maintaining
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for one to two PhD students in analytical chemistry to develop analytical methods for single cell analysis and mass spectrometry imaging using direct infusion mass spectrometry. The PhD candidate will work