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. Qualifications: PhD in machine learning, with experience in applications in computer vision or medical image analysis. Strong publication record in top venues (e.g., CVPR, MIDL, MICCAI, IPMI, PAMI, TMI, MIA
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training and guidance to junior undergraduate and graduate students. Education: A PhD in Neuroscience, Computational Neuroscience, Machine Learning in image analysis, or a related field, with significant
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worldwide, leveraging industry-standard tools and technologies to ensure the quality and reliability of the developed prototype hardware implementation. Qualifications: PhD in Electronics/Computer Engineering
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, computational oncology/biology, kinetic modeling, advanced image processing. The candidate should be highly motivated with a strong interest and commitment to research. Curiosity and creativity with an aim
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at MUN features state-of-the-art medical laboratories equipped with high-resolution confocal imaging, a Seahorse analyzer for metabolic profiling, flow sorters and cytometers, an electron microscopy suite
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. Experience with total internal reflection fluorescence (TIRF) microscopy. Ability to perform image analysis and processing (e.g., ImageJ/Fiji) The following backgrounds are considered an asset or highly