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Field
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Postdoctoral Fellow – X-ray image reconstruction for connectomics Details of the role Reports to: A. Schaefer Sensory Circuits and Neurotechnology Lab Contact term: This is a full-time, fixed term
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standards-compliant power electronic systems. Key Responsibilities: Design and prototype power converters using WBG devices. Conduct simulation and experimental validation on lab and real-time testbeds
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this progression through Optical Coherence Tomography (OCT) imaging places increasing pressure on the NHS, often requiring substantial resources for eyes that may remain unaffected for years. Predicting which eyes
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without triggering autoimmunity. To address this, our research program heavily focuses on studying T and B cell population dynamics through intravital 2-photon imaging and the role of secreted immune
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humans, providing a unique opportunity to work with cutting-edge neurophysiological and imaging techniques. The study will examine age-related differences in motor unit behaviour across multiple muscles
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complete Data management for the project including data collection, cleaning, coding, analysis and interpretation of primary/secondary datasets using statistical software packages collaborate and build a
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the Job related to staff position within a Research Infrastructure? No Offer Description The position is in the Digital Signal Processing and Image Analysis (DSB) research group, Section for Machine
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 2 days ago
the recording of dendritic electrical signals using electrophysiological and imaging techniques. The fellow will be involved in setting the protocol for imaging voltage signals in dendrites of pyramidal
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Responsibilities: To independently undertake research on data-efficient object detection with key techniques in few-shot learning, transfer learning, image synthesis, etc. To produce research reports and/or
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems