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. This research project has a dual focus. On the one hand, you will be involved in analysis of spatial, single-cell and multi-omics data to efficiently characterize the different molecular layers. This will be done
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, that combines diffusion and transformer models, there are clear indications that the analysis of this data can be automated. This will open new avenues in data interpretation and building predictive models
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and analysis, mouse monitoring, drug administration, and tissue collection and processing, as well as a range of molecular biology techniques such as qPCR, Western blotting, ELISA, and
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. Researchers eligible for an FWO or MSCA fellowship are encouraged to apply. Key Responsibilities Lead and conduct the processing and statistical analysis of large-scale short- and long-read sequencing
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motion) Pose tracking and behavior segmentation with tools like DeepLabCut, MoSeq, and Kinect-based systems Longitudinal analysis of behavior from early postnatal to adolescent stages in
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training in light and electron microscopy, as well as image processing and analysis. A dedicated team of microscopists supports the Ghent-based VIB research community, working closely with our sister
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with large-scale data analysis, such as genomics or transcriptomics data Experience with a workflow management system such as Snakemake or Nextflow A willingness to learn and apply machine learning
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artificial intelligence, microelectronics and nanoscience, to microfluidics, single-cell and molecular analysis, functional genomics and cell biology in human cells and animal models. Discover our environment
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, perform and document experiments in an Electronic Lab Notebook (ELN) Optional knowledge Golden Gate vector cloning Analysis of CRISPR/Cas9 edited plants Experience working with cereals (maize, wheat
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analysis Background in biomedicine and digital pathology What we offer Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within