385 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "University of Waterloo" positions at Monash University in Australia
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Advisory System, or data from other implantable or wearable devices. This involves consideration of both feature-based machine learning or data science approaches and neural mass parameter estimation
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Information Technology Industry-Based Learning Placement Grant This grant is awarded to high achieving students in the Faculty of Information Technology who undertake a placement with an industry
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they fulfil the criteria for Masters by Research & PhD admission at Monash University. Details of the relevant requirements are available at https://www.monash.edu/engineering/future-students/graduate-research
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requirements are available at https://www.monash.edu/engineering/future-students/graduate-research/how-to-apply Your application will be looked upon favourably if you: Graduated in the top 10% of your year level
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. Required knowledge Strong background in machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch
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encoded in computer software and can be used as decision support systems (DSS). These may be used by decision-makers with different domains of expertise than the analysts who built the DSS system. Therefore
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The proposed PhD project aims to build a machine learning/deep learning-based decision support system that provides recommendations on precision medicine for paediatric brain cancer patients based
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their performance evaluated in terms of classification accuracy, computational speed, and overall usability. Required knowledge Deep learning (CNNs, Transformers) and computer vision Knowledge distillation for model
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This Masters or PhD project aims to explain the uncertainty of Machine Learning (ML) predictions. To this effect, we must quantify uncertainty, devise algorithms that explain ML predictions and
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Many machine learning (ML) approaches have been applied to biomedical data but without substantial applications due to the poor interpretability of models. Although ML approaches have shown