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PhD candidate to develop the modeling and signal analysis methods that turn nanobubble ultrasound imaging into a quantitative diagnostic tool. You will work with imaging data acquired from lab-grown
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and will contribute to data analysis, experimentation, and preparation of research results. Responsibilities Primary responsibilities include: Implement and evaluate image dehazing and image enhancement
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, membrane integrity) Develop or adapt image analysis and quantification pipelines with AI support to handle screen-scale data Follow up on screening hits to identify their molecular target or mechanism
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-cell RNA-seq, spatial transcriptomics, proteomics, metabolomics, ATAC-seq, ChIP-seq, or CyTOF/imaging mass cytometry. Experience with statistical analysis of large biological datasets and strong
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existing cardiothoracic imaging-AI programme, bringing together automated analysis of the heart, pulmonary vasculature and lung parenchyma with explainable outputs and expert review. You will not be starting
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an appetitive/aversive paradigm Perform wet lab work such as histology/RNA-scope to validate viral targeting and probe gene expression, as well as imaging of the data Perform data analysis on behavioral and
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statistical assessments of the uncertainties of the estimate(s). Essential Job Duties Gather key data from the HST archive and calibrate/process the images such that the quantitative analysis of the atmosphere
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the EU Research Framework Programme? Other EU programme Reference Number 2609/11 Is the Job related to staff position within a Research Infrastructure? No Offer Description Analysis of microscopy images
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multispectral and hyperspectral UVvisible imaging and synchrotron X-ray analysis to map photoluminescent signatures, analyze elemental composition (heavy metals, rare earth elements, etc.) and the chemical
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cell biology, including cell culture, PCR/qPCR, protein analysis, microscopic imaging, and animal handling. One year of molecular lab experience after graduation. Molecular cloning experience is a plus