401 machine-learning-"https:" "https:" "https:" "https:" "https:" "University of St" "St" positions at Monash University
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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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experience with programming (e.g., Python), machine learning, or educational data is beneficial, it is not a strict requirement. The project provides ample opportunities to develop these skills over time. What
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Over the past decades, we have witnessed the emergence and rapid development of deep learning. DL has been successfully deployed in many real-life applications, including face recognition, automatic
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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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econometrics and machine learning, is highly desirable. You are well-organised and capable of managing multiple tasks to meet deadlines, with excellent written and verbal communication skills for producing clear
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Project Manager - PANTHER TRIAL Job No.: 688710 Location: 553 St Kilda Road, Melbourne Employment Type: Full Time Duration: 12 month fixed-term appointment Remuneration: $120,138 - $132,610 pa HEW 8
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Program Manager - BloodCare CRE Job No.: 686995 Location: 553 St Kilda Road, Melbourne Employment Type: Full-time (negotiable from 0.6 FTE) Duration: 12 month fixed-term appointment Remuneration
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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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the brain. This wouldn't be a typical machine learning PhD, as many aspects can only be examined on a philosophical and theoretical level. There may be scope to implement aspects in the ideas you develop
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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