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neurocritical care research The Opportunity We are seeking a Research Fellow - Data Science professional with strong expertise in machine learning, deep learning and high-frequency physiological signal analysis
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the application of AI and machine learning to identify novel therapeutic targets and advance precision medicine approaches. For further information, please click here to view the full appointment
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applies. 2 Fixed-term position available for up to 24 months. Flexible work arrangements can be negotiated with the right candidate. Be part of the Australian Institute for Machine Learning -- the largest
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criteria • Bachelor-level qualification • Australian driver’s licence and access to a car • Excellent organisational and communication skills • Ability to work independently and collaboratively, adapting
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in advanced signal processing techniques and good understanding of emerging machine learning methodologies used in NDE. You will work in close collaboration with project partners at the University
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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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sampling missions design of machine learning systems for real-time obstacle detection, terrain analysis, and environmental adaptation in extreme environments implementation of multi-constraint optimisation
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). Proficiency in numerical modelling, data analysis and instrument control in languages such as Matlab, Python, C/C++, etc. Familiarity with sensor technologies and applications, machine learning, and electronics
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Melbourne CBD campus About the Role We are seeking a Postdoctoral Research Fellow to join RMIT's Materials Modelling and Simulation group to apply classical Molecular Dynamics and Machine Learning approaches