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Field
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, and an interest in computervision, image processing, or machine learning. Experience with cameras or microscopy, motion systems, PyTorch/TensorFlow, GUI development, or test-bench automation is a
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The School of Materials Science and Engineering (MSE) provides a vibrant and nurturing environment for staff and students to carry out inter-disciplinary research in key areas such as Computational
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, Applied Mathematics, or a related field. Strong expertise in: Computer vision and image processing Deep learning (e.g., PyTorch, TensorFlow) Data-driven modeling and analysis Proficiency in Python and
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publications. Coordinate with internal researchers, external labs, and industrial partners. Candidate Profile: Required qualifications : PhD in Mineral Processing, Mining Engineering, Georesources Engineering
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, and reliability prediction of wind turbine blades. Qualifications / Licenses / Certifications Must be a student enrolled at UVU in the Engineering Department Must be interested in signal and image
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involving image reconstruction, image processing, quantitative analysis, and data management. Responsibilities will include processing and analyzing MRI data; implementing and maintaining image
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University of California, Los Angeles | Los Angeles, California | United States | about 2 months ago
Neuroscience, Bioengineering, Computational Biology, Biomedical Engineering, Computer Science or related field (preferred) Minimum 1 year of experience with neuron reconstruction and/or image processing
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. Qualifications Ph.D. or equivalent doctoral degree in Metallurgy, Process Engineering, Materials Chemistry, or a related discipline, with a specialization in pyrometallurgy or mineral thermal processing. Strong
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Profile: Required qualifications : PhD in chemical Engineering, biotechnology or related discipline. Proven experience in mineral characterization, liquid analysis and process development; Strong background
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processing of biomedical imaging, digital pathology, and spatial omics datasets for research projects. - Support computational image analysis, data annotation, and quality assurance activities using