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PhD Scholarship for a Design-Led Research Program on the Future of CT Imaging in Distributed Care Job No: 680923 Location: Caulfield campus Employment Type: Full-time Duration: 3-year fixed-term
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the Faculty, the Department of Electrical and Computer Systems Engineering (ECSE) offers internationally acclaimed programs in power systems, telecommunications, electronics, robotics and biomedical engineering
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seeking a leading researcher to advance a program in Applied Clinical Data Science, Machine Learning and AI. This role offers the chance to lead high-impact projects, mentor emerging researchers, and
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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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the energy market, Role of EVs in the grid, Power System Stability Analysis Using Machine Learning Techniques and more. Eligibility Requirements: Applicants must be Australian citizens or Permanent Residents
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Levin Kuhlmann Research area Machine Learning We are seeking a highly motivated and innovative PhD student interested in exploring the opportunities for using AI to enhance personalisation of services and
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, Engineering or others related to the PhD topic) Excellent programming and/or robotics background, with a keen interest in human-robot interaction Prior knowledge of robotics and machine learning (e.g., relevant
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mechanical loading of such samples. The focus of the PhD project will be to use machine learning techniques to better understand the interplay between the crystal orientations and deformation patterns in a
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This PhD project is part of a larger project that aims to explain the uncertainty of Machine Learning (ML) predictions. To this effect, we must quantify uncertainty, devise algorithms that explain
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, virtual screening, molecular docking, structure-activity relationship analysis, and machine learning. Candidates should embrace opportunities to tackle new problems and challenges as part of a dynamic team