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% and shift work loadings apply. Fixed term position available immediately for a Veterinary Nurse – Equine & Large Animal until 31 December 2025 We are seeking a suitably qualified or experienced
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business units designed to create financially sustainable clinical teaching environments: the Small Animal Hospital, the Large Animal Hospital, and Pathology. The RVH Pathology unit provides both routine and
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to the principles of equity, diversity and inclusion. Desirable characteristics: Experience of handling large sets of samples from multiple collaborators. Experience with HPAEC-PAD, mass spectrometry and HPLC systems
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large courses (>200 students) and the management of teaching and learning resources and staffing Demonstrated experience in innovative teaching methods and curriculum development relating to physiology
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metapopulation and/or individual based models Knowledge of Bayesian methods, including Approximate Bayesian Computation Experience with big data analysis and HPC environments Knowledge of additional programming
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data requirements, and lower costs for large-scale modelling tasks. PINNs enhance predictive capabilities and efficiency by combining data-driven methods with physical principles. Unlike traditional
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of equity, diversity and inclusion. Desirable characteristics: Experience in large data sets and their platforms/tools, cloud-based architectures, and deployment frameworks for machine learning algorithms
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of better prevention and public health policies in rural and remote areas. This position will contribute to the design of qualitative research components, coordinate qualitative data collection from rural
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, epidemiologists, qualitative researchers, pharmacists, Aboriginal health practitioners, consumer representatives). As part of a large NHMRC study, the successful candidate will work with the project coordinators
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Statistics for the Australian Grains Industry 3 (SAGI3). Investment. The University of Adelaide, in collaboration with Curtin University and The University of Queensland, is leveraging machine learning, data