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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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of Sustainable Development at Utrecht University. Where to apply Website https://www.academictransfer.com/en/jobs/363888/phd-spatial-optimization-of-lan… Requirements Specific Requirements We are looking
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at https://biffilab.wordpress.com Pancreatic ductal adenocarcinoma (PDAC) remains a formidable clinical challenge. A major recent advance has been the development of KRAS inhibitors, which have shown
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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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prediction Integrating various types of spatial single-cell data, such as gene expression and protein expression data Developing image analysis methods for histopathological specimens using AI-based models As
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and experimental models to study metabolic communication in GBM invasion. In this context, spatial transcriptomics and mass spectrometry imaging provide tissue-level maps of tumour–microenvironment
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(further funding will be applied for) and focuses on power systems engineering in the context of the next phase of Iceland’s energy transition. It builds directly on established modeling work at Reykjavík
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Network ReDiLEEP (https://redileep.eu/ ). ReDiLEEP brings together leading universities, research institutes, and non-academic partners across Europe and beyond to advance response diversity research and
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network discovery and individualized circuit targeting, multimodal concurrent brain stimulation-recording, and computational modeling. We bridge invasive approaches, including intracranial electrical