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training programme at the start of the PhD to develop skills in areas such as programming, data analysis, machine learning and signal processing. This will provide the technical foundation required to work
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programming (e.g., Python/C++), machine learning frameworks, or robotics software environments such as ROS. You are motivated to work in a multi-disciplinary research environment combining engineering, AI, and
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teaching, particularly in the area of Machine Learning. In addition, you will be expected to contribute to the whole range of teaching and administration across the University’s data science programmes
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, microbial cultures, and cleaning validation samples. Develop data analysis pipelines for Raman spectral classification, potentially integrating machine learning methods. Research & Project Responsibilities
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languages and environments. Experience with machine learning and AI in biomedical settings would be considered favourable. You will also need a problem-solving ability to manage and analyse datasets and the
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using liquid biopsy next generation sequencing data for cancer diagnostics. About You Must have a strong background in next generation sequencing data analysis/machine learning, cancer and/or genome
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an integral part of UWA’s academic community. It will offer various degrees in Computing with subjects across Computer Science, Philosophy and Statistics including software engineering, computer systems
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Professor in Bioinformatics Education to support teaching across our portfolio. It is expected that the post-holder will support teaching in Machine Learning related modules. The post-holder will be expected
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, install, commission and maintain compute and data storage resources supporting the research of the Institute, including Machine Learning. • Assume technical and organisational lead responsibility for one
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will have some prior knowledge in deep learning and computer graphics. Subject area: Statistics, AI & Machine Learning, Public Health & Epidemiology