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excellence and mentoring early career academics Leading staff development, performance and workload equity Expanding the School’s HDR program and fostering interdisciplinary collaboration This role offers
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Collection Acquisition Senior Librarian Job No.: 685533 Location: Clayton campus Employment Type: Full-time Duration: Continuing appointment Remuneration: $96,768 - $104,450 pa HEW Level 6 (plus 17% employer superannuation) Amplify your impact at a world leading University library Join our...
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Research Assistant, Paediatrics Job No.: 685454 Location: Monash Medical Centre Employment Type: Full-time Duration: 12-month fixed-term appointment Remuneration: $83,280 - $113,025 pa Level A (plus 17% employer superannuation) Join world-leading researchers exploring sleep and health in...
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people who discover them The Opportunity Lead a dynamic program of veterinary care, research animal skills training and scientific services at the Monash Animal Research Platform (MARP). At the centre of a
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., Pan, S., Aggarwal, C., & Salehi, M. (2022). Deep learning for time series anomaly detection: A survey. ACM Computing Surveys.
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and evaluate our approaches on a range of computational sustainability case studies from the domain of conservation of biodiversity, natural resource management and behavioural ecology. Relevant
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PhD Scholarship in Generative Artificial Intelligence Job No.: 686325 Location: Clayton campus Employment Type: Full-time Duration: 3.5-year fixed-term appointment Remuneration: The successful applicant will receive a Research Living Allowance, at current value of $36,063AUD per annum 2025...
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people who discover them The Opportunity The Research Fellow will be a motivated and talented computational scientist and a key member of Monash University ice sheet modelling research team and SAEF’s
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explore unconventional ideas, develop computer algorithms for data analysis, create new experimental approaches, and apply the technique in areas like biomedicine, materials science, and geology. My group
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This Masters or PhD project aims to explain the uncertainty of Machine Learning (ML) predictions. To this effect, we must quantify uncertainty, devise algorithms that explain ML predictions and their uncertainty to different stakeholders, and evaluate the effect of the conveyed information. The...