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Field
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conditions, by bridging disciplines, from artificial intelligence, microelectronics, neuroengineering and nanoscience, to single-cell, imaging and molecular analysis, functional genomics and cell biology in
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Mechanisms of EBV-Infected B Cells in Multiple Sclerosis (DECODE-MS)”. We are looking for a highly motivated candidate to undertake a PhD project aimed at understanding the mechanisms by which Epstein–Barr
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The International Institute of Molecular Mechanisms and Machines Polish Academy of Sciences | Poland | about 2 months ago
regulate transcription, chromatin organization, and cell fate. We combine molecular and cellular biology with biochemistry, quantitative imaging, and functional genomics to uncover fundamental mechanisms
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pathogenesis — work with meaningful implications for antiviral therapeutic development worldwide. The Research Technical Assistant will play an essential supporting role in the day-to-day operations of a fast
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project will define cell-cell communication pathways and gene regulatory networks involved in normal and abnormal artery formation. Key findings will be validated in developing embryos and investigated
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project will define cell-cell communication pathways and gene regulatory networks involved in normal and abnormal artery formation. Key findings will be validated in developing embryos and investigated
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, CRISPR-Cas9, single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (RNA-seq), multispectral imaging, immunohistochemistry, Western blotting, tissue culture, genotyping, and qPCR. Under
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of biomedical imaging data; AI-based prediction of cell and exosome distribution in regenerative biomaterials. The candidate will receive interdisciplinary training in biomaterials research, advanced imaging
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CoE (https://www.med.uio.no/hth/english/ ) is inviting applications for a three‑year PhD position. The recruited candidate will take part in UiO Emerging Technologies Initiative Project FTI-NAM. NAM
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The candidate will develop and benchmark zero-shot multimodal fusion models for rare disease prediction, using melanoma as a use case. The project integrates spatial and single-cell multi-omics data with