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Field
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on AI-enhanced automation of transmission electron microscopy imaging and spectra acquisition, developing AI protocols based on ML, DL and computer vision within the project EDISON. Main Tasks and
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MSc/PhD Position at the Faculty of Medicine, Memorial University of Newfoundland, St. John’s, Canada
-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 with advanced tissue
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and performing laboratory (wind-wave facility) experiments, using state-of-the-art imaging techniques developing computational codes to process and understand large experimental datasets (e. g., image
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of electron microscopy imaging and spectroscopy to reveal the structure–property relationships that govern molecular adsorption mechanisms. This interdisciplinary project is fully funded by DTU’s PhD grant
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and hands-on experience with AI and computer vision. Solid programming skills in Python, especially with PyTorch. Practical experience with deep learning projects, including working with attention
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management skills. Candidates with laboratory skills and imaging are desired for this project. Must be eligible to enrol in PhD programs at Curtin. Application process Please send your CV, academic transcripts
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degree in biomedical sciences or related life science discipline We are looking for candidates with hands-on experience or a strong interest in spectral imaging techniques, confocal microscopy, and
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for candidates with hands-on experience or a strong interest in spectral imaging techniques, confocal microscopy, and bioinformatic analyses Experience in mouse work is highly desirable Interest in
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array antenna systems for imaging MIMO radar in autonomous driving applications. This work will advance the design and characterization of intelligent devices and environments for wireless communications
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transfection work Experience with microscopy Experience with RNA-seq Experience with image and RNA-seq analysis, including competence using R or python and computational clusters Molecular biology techniques