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applications in engineering areas. additional background or experience in machine learning, data analytics, and other computer science areas would be an advantage experience in power system simulation software
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physical attributes will support and improve the mapping of seagrasses. · Develop machine learning models and object-based image processing algorithms to differentiate and identify seagrass habitat
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, computer science, computer vision, or a related domain (a background in medical imaging is advantageous) Proficiency in Python programming or familiarity with deep learning frameworks like PyTorch
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Department of Mechanical Engineering. The successful candidate will have strong interest in computer vision, AI and/or robotics techniques. A programming skill (e.g., Python) would also be essential. They will
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considered, but it will further be required that they also have a strong interest in operations and supply chain management background. Knowledge of optimization solvers and Proficiency in machine learning
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Proficiency in machine learning algorithms and their practical implementation in Python would enhance the qualifications. Stipend: The scholarship will be for 3.5 years and has a stipend of $34,210 (2024 rate
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that relate to this PhD project: Computer Vision / Augmented Computer Vision Machine Learning Electronics mini/micro portable devices design UAV navigation and automation There are many fields that relate
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intelligence, Machine learning, and Computer vision for subsurface characterisation This project aims to develop computer vision applications for geological characterisation using state-of-the-art AI/ML methods
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Machines Pty Ltd, so you may be eligible to apply for a stipend top-up via the National Industry PhD Program . If you're an international student, you will also receive a tuition fee sponsorship for your
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Reducing aerodynamic noise of advanced air mobility by prediction based on machine learning 2 Minute read This PhD project will be based at the University of Melbourne with a 12 month stay at