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experts, using machine learning and modern analytical techniques to build high‑impact, Python‑based products that guide strategic decision‑making across the institution. Key responsibilities: Partner with
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related discipline): Computer Science, Artificial Intelligence, or Machine Learning Economics or Econometrics (particularly applied micro, behavioural, or decision-focused modelling) Applied Mathematics
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. About the opportunity Apply cutting‑edge data science, computer vision, deep learning, and generative AI to agricultural and phenomics research across UWA, DPIRD, and national APPN partners. Coordinate
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guidance system, informed via MR of information necessary to complete the task, but also able to supervise any machine-learning or decision-making processes. This is an ambitious goal involving many sub
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& inclusion Enjoy a career that makes a difference by collaborating & learning from the best At UNSW, we pride ourselves on being a workplace where the best people come to do their best work. The School
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work integrated learning (WIL) placement and are required to relocate from your normal place of residence struggling financially and are unable to meet the costs of placement able to demonstrate genuine
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distributions. We wish to represent the biological networks into proper formats, e.g., vector representations, so that existing machine learning algorithms (e.g., support vector machines) can readily be used
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and Boulton, 1968; Wallace and Dowe, 1999a; Wallace, 2005) is a Bayesian information-theoretic principle in machine learning, statistics and data science. MML can be thought of in different ways - it
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. This work combines computational modelling and simulation with biological experiments that are analysed using cutting-edge computer vision techniques. We collaborate closely with Macquarie University where
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systems. The fast growth, practical achievements and the overall success of modern approaches to AI guarantees that machine learning AI approaches will prevail as a generic computing paradigm, and will find