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with the study of diabetic neuropathy, animal models, using cutting-edge imaging technologies such as confocal microscopy, laser speckled imaging (LSI), transmission electron microscopy, nail bed
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sequencing (snRNA-seq) and spatial transcriptomics experiments on post-mortem human brain tissue and animal models. Sample processing. Bioinformatic analysis of the data generated in R and/or Python
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-clinical rodent models — supported by advanced in vivo perfusion imaging and single-cell/spatial molecular profiling — to study impaired diabetic and ischemic wound healing and to develop tissue
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Full-Time Fixed-Term for 36 months This PhD aims to develop novel robotic monitoring and data processing methods to document changes in dynamic seafloor environments over large spatial scales
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modelling. References/further reading Wang, X. Q. et al. Spatial predictors of immunotherapy response in triple-negative breast cancer. Nature 621, 868-876 (2023). Danenberg, E. et al. Breast tumor
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developed mouse models and human tissue processing pipelines. The candidate will learn and use cutting edge immunological methods (high parameter flow cytometry, multiplex imaging, single cell and spatial
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on single-cell and spatial genomics data, from sequencing and imaging, and apply them to human developmental and disease biology. Possible research directions include: ● Generative models of cell–cell
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using various model systems (BIO ). For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/308656/phd-fellowship Where to apply Website https://www.jobbnorge.no/en/available
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Computational pathology and digital pathology using whole slide imaging (WSI) Spatial biology, spatial transcriptomics, and multi-omics data integration Large language models (LLMs) and foundation models
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at the interface of biophysical modeling, soft matter and cell mechanobiology at the Groningen Research Institute of Pharmacy, within the Faculty of Science and Engineering at the University of Groningen. What