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(e.g., tensor or multi-modality data). Work with other researchers and PhDs to develop AI applications related to image processing, computational imaging as well as computer vision. Lead a team of junior
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resources. In this particular PhD-position you will have the opportunity to develop, optimize and validate advanced MR metabolic imaging methods, for 3T and 7 Tesla MRI, that provide quantitative maps
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Supervisors: Prof Ioan Notingher (School of Physics and Astronomy) Dr George Gordon and Dr Abdelkhalick Mohammad (Faculty of Engineering) Funding: fully-funded (stipend and PhD fees) Start date
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the FHNW. The goal is to develop a highly automated, reproducible pipeline for the capture, processing, and dissemination of 3D digital twins of cultural artifacts using cutting-edge imaging and
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will work with faculty, staff, and PhD students to troubleshoot and resolve problems with computer hardware and software applications on school issued desktops, laptops, and tablets. This position
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processing, memory & plasticity, decision making, and social interactions. Main Duties and Responsibilities Perform the following activities in conjunction with and under the guidance of the Principal
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& Sciences (SCMMS) provides an outstanding multi-disciplinary environment for the pursuit of cutting-edge cardiovascular and metabolic research (https://www.kcl.ac.uk/scms ). We study the fundamental molecular
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advanced phenotyping, imaging technologies, AI-based analyses, and digital twins. The PhD candidate will work on spring wheat genotypes adapted to Norwegian and northern European growing conditions
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motivated Preferred Qualifications: Experience with serial section EM Histology Viral and immuno labeling Stereotaxic surgery Image analysis software and systems (e.g. FIJI/ImageJ, EyeWire) Light microscopy
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automation integration and deployment of image segmentation algorithms for the automated assessment of thin-film solar cell fabrication processes (e.g. layer quality, defects, morphology) within NOMAD Oasis