174 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" positions at University of Sydney
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delivery of practical teaching and simulation-based learning & assessment coordinating staffing, scheduling and operational planning for clinical skills education building strong relationships with health
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an equivalent discipline) expertise in statistical and machine learning approaches, with the ability to apply advanced methods to complex environmental and agricultural datasets proficiency in R and/or
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, perspectives and pedagogies across teaching and learning, and to working in partnership with Aboriginal and Torres Strait Islander communities and Aboriginal Community Controlled organisations to improve health
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responsibilities will be to: engage in high-quality teaching and learning experiences which meet the University’s expectations and standards for education promote affiliate and supervisor engagement in the Sydney
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modules that embed AI and/or machine learning within core curricula, employing tools being deployed in legal practice in Australia and/or abroad Undertake excellent, original research in law and technology
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Full time, 3-year fixed term position, located on the Camperdown Campus at the School of Mathematics and Statistics Opportunity to make significant contributions to teaching and learning practice
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: Using big data insights to optimise the manufacturing process The second phase of this project will focus on processing and utilising machine-learning techniques to analyse large volumes of data from
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communication skills in English strong familiarity with standard computer methods (Word. Excel, PowerPoint), statistical and graphics packages Desirable: experience with rodent handling and surgery experience in
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such as Power BI, Excel, and PowerPoint for diverse audiences. Employ advanced analytics techniques, including machine learning, to forecast trends and support data-driven decisions. Collaborate across
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‑quality learning experiences that meet the University’s standards for contemporary, evidence‑based dental education · develop, review and innovate teaching approaches, ensuring continuous improvement