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genetic variation into elite germplasm. This will require the integration and optimization of several technologies, including genomics, machine learning, genetic simulation, and speed breeding. This is a
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are looking for a Postdoctoral Research Fellow who has: a PhD (or in near completion) in the relevant fields of Artificial Intelligence, Machine Learning, HCI demonstrated contributions to publications in top
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metagenomics, metabolomics, machine learning, and modelling. Your statistical knowledge and data management practices support reproducible, high-quality research. You have a growing publication record, strong
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, and a PhD research program with over 120 students. 40 academic staff conduct experimental research in many areas of Psychology, including behavioural and cognitive neuroscience, perception, learning
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to engage with multidisciplinary teams and external partners. Desirable attributes include experience with spatio-temporal models, machine learning, Bayesian methods, and knowledge of environmental exposure
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an advanced AI-augmented digital platform (AiCT-Med) powered by cutting edge machine learning models trained on multiple large, aged care datasets from providers across Australia. The platform is designed
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closely with researchers and developers, you will help identify challenges, propose solutions, and improve user interfaces based on feedback and testing. You can learn more about the Australian Internet
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-sensor hyperspectral data for crop disease detection and monitoring. Develop machine learning or physics-informed models to retrieve reliable spectral and/or biophysical features, from multi-scale
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an opportunity for a Postdoctoral Fellow. You will contribute to UNSW’s research efforts in developing machine learning algorithm for photovoltaic applications and utilising them for the investigation
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Control” (DP250101137). The Postdoctoral Research Fellow is expected to undertake research on control theory and machine learning techniques for project DP250101137. The Postdoctoral Research Fellow will