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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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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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is highly complex. For the proposed PhD project, experimental data are already available that bring together maps of orientations of such crystals together with the deformation pattern generated during
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ecosystem interactions. If used wisely for decision-support, these technologies can help select and implement effective policies. This PhD project, jointly offered by Monash University (Australia) 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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of Machine Learning (ML) models across large-scale distributed systems. Leveraging advanced AI and distributed computing strategies, this project focuses on deploying ML models on real-world distributed
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to pursue higher degrees such as a Master of Philosophy or PhD. Committed to lifelong learning, the Department supports the professional growth of radiographers, radiation therapists, and nuclear medicine
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would suit a mathematics or computer science student with a background in continuous optimisation (linear and non-linear programming) and discrete optimisation (mixed integer programming). An ability
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research priorities. About You Essential Qualifications and Experience A medical specialist qualification in an area of expertise relevant to the Sub-Faculty and Alfred Health. PhD or equivalent research
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Experience Medical specialist qualification relevant to the Sub-Faculty and Monash Health. A PhD or equivalent research doctorate in a relevant medical or health-related discipline. Senior academic standing