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for high-dimensional dependent data, and data sketching approaches for massive data. Opportunities to Contribute: Develop statistical/machine learning methodology for multi-modal imaging data integration
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Your position We combine mouse tumour models, immunology, molecular biology, flow cytometry, imaging and single-cell approaches to investigate how neurons, immune cells and stromal cells communicate
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Qualifications This position requires a PhD in Computer Science, Electrical Engineering, Artificial Intelligence, Biomedical Imaging, Computational Biology, or a closely related field. Research Record: A strong
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routes — your work anchors the electrification of process heat line. You join the Electrical Energy Systems group, collaborating closely with PhD students, postdocs, and process and materials partners in a
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the future. The Institute brings together researchers in life and physical sciences, and engineering, to develop a spectrum of tools which we will use to image, interpret and intervene in biological systems
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microscopy, computer vision or parallel ML). Domain Knowledge: Experience working with biomedical imaging is highly preferred, with a particular emphasis on electron microscopy (EM) data. Communication
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to cutting-edge research on spectral CT, quantitative imaging, and artificial intelligence. Position Highlights: - Research Focus: Engage in impactful research, focused on spectral CT, quantitative imaging
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intracranial EEG data from animals. Performs advanced signal processing and time–frequency analyses of neural recordings. Develops and implements computational pipelines using MATLAB, Python, or similar
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This position offers the opportunity for a recent PhD in art history or a related field of visual study to enter the field of academic museum education. At the Herbert F. Johnson Museum of Art, we
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(minimum 80% FTE) Reporting to Professor Rachel Upthegrove, you will work specifically on analysis of two completing trials with clinical, biomarker and imaging data: Psychosis Immune Mechanism Stratified