360 data "https:" "https:" "https:" "CMU Portugal Program FCT" positions at Monash University
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traditional and advanced optimization techniques, including analytical models, simulation-based approaches, and data-driven algorithms. The research also considers practical constraints such as cost, process
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While deep learning has shown remarkable performance in medical imaging benchmarks, translating these results to real-world clinical deployment remains challenging. Models trained on data from one
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information on our practice-based PhD program, please see: https://sensilab.monash.edu/work-with-us/practice-based-phd/
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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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of techniques it offers, making ML seem an excellent tool for any task that involves building a model from data. Nevertheless, ML makes an implicit overarching assumption that severely limits its applicability
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-reported data. While informative, self-reported data can be susceptible to bias, poor memory, and incorrect self-assessment. This project will complement this self-reported measurement of feedback literacy
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trends that started earlier in other time series. Part of what will be done will be to identify sufficiently similar time series - and to pool (or combine) relevant data. One of the approaches that will be
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/scholarships/scholarship-policy-and-procedures The Opportunity This PhD scholarship forms part of a collaborative research program on digital transformation, data practices, and everyday life in Indonesia
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and maintenance of information systems and digital services using a wide variety of tools and platforms, including but not limited to web, mobile, conversational AI and cloud infrastructure. This is a
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the observer. Active Goal Recognition extends Goal Recognition by also assigning the data collection task to the observer. This Ph.D. project will provide a unified probabilistic and decision-theoretic