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learning (AI/ML) being a major focus. Many of the laboratory's interests center around the identification of small molecules using mass spectrometry data, and the use of language models to predict
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biology, analytical chemistry, evolution, and data science. The workplace offers access to state-of-the-art core facilities for advanced microscopy and cytometry, cell and molecular biology, extracellular
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Are you an ambitious researcher looking for your next challenge? Do you have a background in operations research, optimisation, or analytical modelling for decision support? Do you want to further
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EEE to support research and development for AiBBLe, an AI-enabled brain-based learning platform, with emphasis on AI for learning, intelligent educational systems, human-centred AI, multimodal analytics
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road safety analytics framework. The role involves integrating multi-source transport datasets, developing advanced analytical and machine learning models for risk identification, and supporting
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, data-driven road safety analytics framework. The role involves integrating multi-source transport datasets, developing advanced analytical and machine learning models for risk identification, and
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 1 day ago
relevant to the fields of data science, data analytics, statistics, machine learning, bioinformatics, or quantitative biology. To be considered to be appointed at Academic Level B, candidates should provide
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 1 day ago
innovative research in the fields of data science, data analytics, statistics, machine learning, bioinformatics, or quantitative biology. They should also present a vision for the activities they will
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posed by traditional compendial methods. Despite RMM having a shorter incubation period, the dependency of RMM on cells, high operator complexity and challenges in integrating process analytical
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. The successful applicant will be expected to design and implement analytical and interpretability frameworks to investigate the internal representations and decision-making processes of machine learning models