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optical image, visual optics, and bio-medical implants. The Centre brings together a multi-disciplinary team of over 20 PhD and Post-Doc researchers in manufacturing engineering, instrumentation and optics
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multidisciplinary team specializing in medical imaging and algorithm development. Our work focuses on advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities
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and functional analysis of the Ryanodine Receptor (RyR). The selected candidate will bring advanced expertise in biochemical & molecular biology, fluorescence spectroscopy, and confocal imaging
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at the molecular and cellular levels to global processes at the ecosystem level. The subject is divided into a range of sub-disciplines and specializations. The PhD program at the Department of Biology includes many
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to explore include mono-chromatic and multi-chromatic illumination, structured illumination, and telecentric illumination distortions. Computer based image analysis approaches will be developed, including
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. for students in the new Bioengineering PhD program), including the design of custom microscopy setups for specific imaging applications. This position will be appointed at the rank of Professional Specialist
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of small pixels and spectral requirements), interferometric techniques rely on comparing an interferogram imaged by the detector array with a simulated interferogram prior to detection. Through processing in
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(Casson lab, https://www.sheffield.ac.uk/biosciences/people/academic-staff/stuart-casson) to develop the first comprehensive picture of chloroplast replication. In addition to opening up a new dimension of
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: (1) automated reconstruction of a visual and geometrical 4D Digital Twin based on visual computing; (2) usage of information from digital imaging techniques for estimation and prediction of current and
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PhD student at ILL on Advanced Neutron Imaging for Defect Mapping in Repaired Aero-Engine Components
underexplored. The aim of this PhD project is to develop and apply advanced neutron imaging methodologies in order to establish quantitative links between processing conditions, microstructural evolution