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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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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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strong background in artificial intelligence, machine learning, and data analysis. Additionally, experience in healthcare informatics, user experience research, and a commitment to improving mental health
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to load any pages, check your computer’s network connection. If your computer or network is protected by a firewall or proxy, make sure that Firefox is permitted to access the web. You can continue with
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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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Materials (IFM), Deakin University. This project will develop solid electrolytes using combined machine learning (ML), molecular modelling, and experimental characterisation methods. We are looking
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of optimization solvers and 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
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). It’s a chance for you to get help with enrolment, learning skills, language expectations and our technology and teaching systems. You will receive program information to your student email. Introductory
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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