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PhD Scholarship Opportunity - Processing intelligence for green metals using in situ X-ray characterisation and machine learning Job No.: 693787 Location: Clayton campus Employment Type: Full-time
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at developing methodological contributions at the intersection of computer vision, multimodal learning, predictive world models, embodied AI, and human-robot interaction. The candidate will work towards models
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PhD candidate will have: A strong background in computer science, artificial intelligence, machine learning, or a closely related field. A solid understanding of machine learning concepts, particularly
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publications in established machine learning, computer vision, artificial intelligence, and robotics venues. Depending on the contribution and maturity of the work, relevant conferences include NeurIPS, CVPR
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applicants with a background or experience in: • Computational chemistry • Materials simulation • Scientific machine learning / AI • Molecular dynamics or DFT • Materials science or a related discipline
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with one of the following doctoral research projects. 1. AI-Aided Site Reconnaissance and Rapid Assessments for Settlement Upgrading How can spatial analytics, remote sensing, and machine learning models
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check the minimum entry requirements for the PhD . Applicants must also satisfy Monash’s English Language Proficiency requirements; Demonstrate knowledge of machine learning, medical image analysis
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experience, deemed equivalent by the GRC (or delegate). The ideal PhD candidate will have: A strong background in machine learning, deep learning, and signal processing Proficiency in Python and machine
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should ideally have experience in: Essential Deep learning and machine learning Computer vision Python programming PyTorch or TensorFlow Strong mathematical and analytical skills Desirable Video
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computer science, information technology, artificial intelligence, machine learning, software engineering, computer/electrical engineering, or a closely related discipline. This PhD project is part of a