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confocal, and super-resolution microscopy to perform live-cell and fixed-cell imaging. Apply advanced image processing using ImageJ, Matlab, and other platforms. Interpret complex imaging datasets and
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the schools of Cardiovascular and Metabolic Medicine (SCMMS) and Biomedical Engineering and Imaging Sciences (BMEIS) at King’s College London (St Thomas’s Campus). The post will suit someone with a PhD in the
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insights into giant planet auroral processes. You will engage in leading-edge research and contribute to high-impact publications, while also representing the research team at national and international
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member of either our Electrical Power or Fluid Mechanics research nodes. The Electrical Power Research Node comprises a group of eight academics with seven research associates and 20 PhD students. We have
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established research groups investigating the spreading of alpha-synuclein aggregates and their functional and tissue-level impacts using histological, transcriptomic, behavioral, and in vivo PET imaging
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biological assays and data analysis. Tissue Collection and Processing: Handle tasks related to tissue collection, processing, preservation, sectioning, immunostaining/IHC, and imaging. Lab Management: Maintain
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patients for clinical trial participation. Experience in multi-modality treatment planning (e.g., PET, 4D CT, MRI), image guided radiotherapy (IGRT) and stereotactic body radiotherapy (SBRT) and stereotactic
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the presence of photosensitizers. Conduct imaging studies in giant unilamellar vesicles (GUVs) to validate the impact of deuterium content in the lipid membrane to mitigate the photosensitizer activity. Conduct
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learning algorithms focused on image data, natural language processing, and tabular data Conduct exploratory data analysis and feature engineering for high-dimensional datasets, including image, text, and
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biomedical sciences). Examples of topics of interest include the investigation of fundamental biological processes at the molecular, cell or organismal levels; disease modeling and pathophysiology