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samples. This will involve tunnel-diode resonators, real-space magneto-optical imaging, and quantum magneto-sensing using NV centers in diamond. It will also include more conventional thermodynamic and
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strong technical expertise in deep learning, such as models for image segmentation, classification, multi-modal processing, foundation models, or agentic frameworks. An extensive background in computer
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for developing novel diagnostic, imaging, and therapeutic strategies. Our program uses peptide- and antibody-based combinatorial library selection to discover, validate, and exploit the vascular biochemical
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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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for analysing spatial omics and histology data from kidney tissue integrate imaging and molecular data to study how spatial patterns within tissue relate to graft health and disease work with clinical
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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
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, you will work specifically on analysis of two completing trials with clinical, biomarker and imaging data: Psychosis Immune Mechanism Stratified Medicine Study and the Antidepressant for Prevention
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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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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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Yale Analog and RF Circuits and Systems (ARCS) Research Group, Department of Electrical and Computer Engineering, Yale University The Analog and RF Circuits and Systems Research Group in