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mathematical modelling Machine learning and/or other quantitative modelling in AI Statistical modelling Numerical analysis and scientific computing. The posts are full-time and are fixed term for a period of up
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. Scientific and Technical Competencies: • Strong background in machine learning, deep learning, and time-series modelling, with engineering applications. • Experience in prognostic modelling (e.g., RUL
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analytics (with expertise in data exploration and data engineering), probability and statistics, machine learning, data visualization, database management systems, data mining, predictive analytics, and
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 1 day ago
experience applying data science, statistical modelling, machine learning, or bioinformatics methods within research or applied settings, ideally alongside the development of reliable and well-documented
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the progression of ARDS in intensive care patients with sepsis. To enable this, we will develop information-theoretic machine learning methods to determine which protein interactions are driving disease progression
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you passionate about advancing Machine Learning by integrating
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modeling and skilled in numerical simulations, will design a mesoscopic radiative model aimed at overcoming the CFL constraint and exploring machine learning methods and neural operators to address
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of machine learning to the practical tools of deep learning, now available through modern foundation models. For the theory part, the selected candidate will work in close collaboration with
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the foundational mathematics and programming skills necessary for creating basic neural networks and deep learning models from the ground up. Additionally, it is designed for those keen on comprehending
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quantitative discipline or equivalent experience. · Experience applying statistical or machine learning methods in real-world contexts. · Proficiency in Python and/or R for data analysis and modelling. · Strong