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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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tools and concepts. Supervise student projects and BSc/MSc theses. Your Profile: Master’s degree in physics, electrical/electronic engineering, computer science, mathematics, or a related field. Strong
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of software tools and concepts. Supervise student projects and BSc/MSc theses. Your Profile: Master’s degree in physics, electrical/electronic engineering, computer science, mathematics, or a related field
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DEPARTMENT OF HEALTH TECHNOLOGY AND INFORMATICS Research Assistant Professor in Medical Laboratory Science / Biomedical Science / Medical Imaging and Radiation Science / Medical Physics / Medical
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use this formalisation to encode our STV algorithm on encrypted ballots. This approach aims to ensure both the correctness and privacy of the tallying process, paving the way for verifiable and secure
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harness advanced techniques such as machine learning, optimization algorithms, and sensitivity analysis to automate and enhance the mode selection process. The result will be a scalable methodology that
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simultaneously, useful for printing functional devices. Discovering the interactions of these materials and how to leverage this advanced manufacturing process will open new opportunities: devices with variable
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world-class laboratory facilities in the CfAM engaging with interdisciplinary team with expertise in 3D printing, biotechnology, physics, and materials science. PhD project description: Responsive 3D
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of the application process may contact, in confidence, accessibilityrequest.hr@mcgill.ca .
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stacking, both high performance and (very) high density can be achieved by this concept. The mission will be to explore, understand and develop the fundamental physics of device operation. This will require