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practices. The findings will serve as the empirical foundation for the security framework. Defensive Strategies: Propose and prototype new defensive architectures and techniques that can be integrated
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for imaging Apply for this job See advertisement About the position Position as PhD Research Fellow in machine learning available at Department for Informatics with the research group Digital Signal Processing
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,USA and Europe nationals. You will be part of a world-leading team in correlative in situ imaging of advanced manufacturing processes, with strong links to synchrotron facilities and industrial
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the group's research on developing novel machine learning/computer vision methodology. The focus of this project will be on the development of deep learning methodology for spatio-temporal medical image
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allows for studying language behaviour (time-course and quantity of gaze/eye-movements), neuro-physiology of language processing in the brain and neuro-imaging (https://www.ntnu.edu/langdevlab#/view
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fields. Strong background in medical image analysis and signal processing. Proficiency in programming, particularly in Python. Demonstrated ability to publish in peer-reviewed journals. Motivated, self
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experience performing in vivo biodistribution imaging to apply to an exciting project investigating antibody penetration in heterogenous tumor models. The postdoc will work closely with in vivo imaging
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(hiPSCs), cardiomyocytes, metabolism About the project We are recruiting a postdoc (established or newly graduated from their PhD) who has an exceptional ‘can-do’ attitude, with drive and enthusiasm to push
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practical workshops, and we recently partnered with KCL’s Spatial Biology Facility , an advanced centre equipped for high-resolution spatial transcriptomics and multiplex imaging, to turn large-scale data
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, operation of the scanner, data acquisition and analysis, image evaluation, and statistical analysis. The fellow will also be expected to prepare manuscripts and conference abstracts related to projects and