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. Knowledge of statistical methods commonly used in single-cell and spatial omics, such as Seurat and Scanpy. Experience with machine learning models, such as transformer and diffusion models. Strong written
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and Host Area The School of Computing has a strong foundation in computing and information sciences at ANU. We are a transformative centre for research in artificial intelligence and machine learning
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servicing missions. Experience with machine learning techniques for robotic decision-making and intelligent control for tasks with high uncertainties. Experience with research on multi-agent collaboration and
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are looking for candidates with interests in the use ultracold quantum gases on optical lattices to simulate models from condensed matter physics. Candidates should submit a CV, statement of research interests
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enhance our contribution to society. Responsibilities* The successful candidate will work on projects performing analysis of PET neuroimage data, including kinetic modeling and multimodal data synthesis
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transportation operations and network modelling, accessibility analysis, data analysis (statistics and/or machine learning methods), and spatial mapping. Because the work will involve multiple years of daily
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and machine learning to optimize treatment conditions. Contribute to the development of reproducible stress priming methods and assist in transferring knowledge to agricultural stakeholders. Required
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), clinical trials, disease surveillance, and the use of novel methods including Bayesian network, machine learning, social network analysis and dynamic data visualisation tools. Further information is
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, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and grow'. We welcome you to join our community
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simulations using DFT (particularly of surface processes); kinetic Monte Carlo simulations; molecular dynamics simulations; classical and machine-learned force fields. Highly developed skills in scientific