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novel opportunity to automate and improve the frailty assessment process, aiming for greater consistency and predictive accuracy. Aims i) Develop a deep learning algorithm to autonomously detect and
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Zhongzheng Wang as your proposed principal supervisor, and copy the link to this scholarship web page into question two of the Financial Details section. About the scholarship Background Two PhD positions
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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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to the effective supervision of Honours and Higher Degree by Research (e.g., PhD, Masters) students (as appropriate). Demonstrate personal effectiveness in supervision and the management of researcher development
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techniques for near-field microwave systems, design and test antennas/antenna arrays for near-field microwave imaging, model and simulate antenna and algorithm performance, participate in lab testing, write
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. The tasks of the postdoctoral researcher (innovation) will include: Conduct world-class research in foundational AI, with a focus on applications in the financial sector. Develop innovative algorithms
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to research-based activities, including the development of new data analysis algorithms, processing and analysis of field data, and participation in the fieldwork. Your responsibilities will include: Conduct
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to management and analysis of complex data sets. Data Management research storage, indexing and querying of complex data algorithms for managing big data efficiently at scale Big Data Processing, including
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research related to management and analysis of complex data sets. Data Management research storage, indexing and querying of complex data algorithms for managing big data efficiently at scale Big Data
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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