10 machine-learning-postdoc Postdoctoral positions at University of Sydney in Australia
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ternary neural networks using FPGA devices. The successful candidate will have significant experience in machine learning, FPGA design and an outstanding track record in conducting machine learning research
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/AI expertise) systems Engineering or Control Systems (with applications to large-scale projects) artificial Intelligence / Machine Learning (with interest in applications to megaprojects or governance
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Postdoctoral Research Associate in Global Environment Modelling of Soil Organic and Inorganic Carbon
. The project is aimed to improve our in-house developed process-based computer model and use it to represent the soil ecohydrological and biogeochemical interactions across various carbon and nitrogen soil pools
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: developing and testing new approaches to water resources modelling, application of Bayesian inference methods to environmental problems, machine learning and data science applications, undertaking analysis and
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, and we are continuously working to identify and remove biases and barriers to make our workplace open, supportive and safe for everyone. To learn more about the School of Chemistry, click here About you
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an environment where individuality is welcomed and celebrated To learn more about the School of Geosciences, click here About you The University of Sydney values courage and creativity; openness and engagement
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-series data interest and experience developing and working with open scientific software interest in analyzing the dynamics of complex physical systems interest in using statistical learning to infer
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methodologies for neuroimaging data pre-processing and analysis; with a motivation to learn new techniques and keep up-to-date with best practices. Publication and Dissemination: Prepare research findings
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. Our mission is to develop life-changing treatments for glaucoma and other optic nerve diseases that cause irreversible blindness. Learn more about the Snow Vision Accelerator: https
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prizes and awards to individual staff members and the award of over $7 million in research funding each year. Our staff are also recognised for their outstanding commitment to teaching excellence. To learn