383 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" uni jobs at Monash University
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This research project aims to address the critical need for privacy-enhancing techniques in machine learning (ML) applications, particularly in scenarios involving sensitive or confidential data
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significant step forward in machine translation capabilities. However, "NMT systems have a steeper learning curve with respect to the amount of training data, resulting in worse quality in low-resource settings
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programming skills and a good background in maths. This project would set you up for a follow-up honours project in this area. https://github.com/cormackikkert/CEGARBox https://github.com/cormackikkert
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career trajectories. The goal is to design better incentives for scientists to produce their best work. Our research group studies how groups of agents can learn to cooperate. Most of our research focuses
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. Scientific Contribution Our group has strong publication record of 100+ first or senior author top-tier (ERA ranking A*/A) journals and technical conferences in the machine learning and medical AI field. His
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Adversarial Machine Learning (AML) is a technique to fool a machine learning model through malicious input. Due to its significance in many scenarios, including security, privacy, and health
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based on matched-filter statistics. Detecting the unknown relies on the development of complex algorithms at the forefront of statistics, machine learning, and data science. This multi-disciplinary
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. Required knowledge Python programming Machine learning background Image analysis Video analysis Audio analysis
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find some of our publications here: https://i.giwebb.com/research/computational-biology/ Required knowledge A solid grounding in artificial intelligence and machine learning. Learn more about minimum
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There is an opportunity to prototype interactive muscle memory systems and study their use in order to understand what designers can learn from remembering activities that involve the active human