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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 | about 18 hours ago
working with real data, and a substantial commitment to reproducible and transparent workflows. They should also have evidence of experience relevant to the fields of data science, data analytics
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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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across records. Develop a cloud-based verification platform for digital data collection and real-time analytics. Develop and apply non-destructive testing (NDT) methods and data-driven approaches
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the baseline data sets and analytics approaches currently employed Development of a proof-of-concept tool, which will provide a single point of access for historic data and records, analyses tools and a RAG-type
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skill in analytical instrumentation and related methods Strong command of technical writing, data reporting, and quality assurance/QA-QC practices Candidates with the following would have an advantage
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synthetic organic chemistry and/or transition metal catalysis in advanced institutions. The candidate should possess analytical skills including NMR, GC/HPLC, mass spec, etc, as well as experience in handling
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with positive therapeutic outcomes (critical quality attributes, or CQA). This interdisciplinary team comprises engineers, biologists, clinicians, manufacturing, and data analytics experts from multiple
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analytics, and control in power distribution systems. The selected candidate will work very closely with partners from utility companies and national labs, and use real utility data and models to address