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p.a. plus 17% super Join the ARC Centre for the Mathematical Analysis of Cellular Systems Develop and apply statistical/machine learning methods to analyse biological data. Salary packaging, subsidised
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nonautonomous dynamical systems, spectral analysis, machine learning, data-driven dynamics, stability/perturbation theory/rigorous numerics. Possible applications of the new theory include the analysis
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multidisciplinary teams of mathematical, computational, and biological scientists to develop and apply statistical and machine learning methods for analyzing complex and large-scale biological data. This position
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Statistics, MACSYS Salary: Level A - $83,468 - $113,262 p.a. plus 17% super Join the ARC Centre for the Mathematical Analysis of Cellular Systems Develop and apply statistical/machine learning methods
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-doctoral fellow, you will collaborate with multidisciplinary teams of mathematical, computational, and biological scientists to develop and apply statistical and machine learning methods for analyzing
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discipline) PhD in in Computer Science, Electrical and Electronic Engineering, Mathematics, or a related discipline (or near completion). Recent relevant research experience in machine learning/deep learning
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Engineering, Mathematics, or a related discipline (or near completion). Recent relevant research experience in machine learning/deep learning. Strong publication record commensurate with career stage and
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where appropriate. About You PhD in the broad area of Computer Science/Engineering and/or Applied Mathematics Detailed and highly specialised knowledge and understanding of Computer Vision, Deep Learning
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, mathematical, and computer modelling skills. Excellent interpersonal communication and oral presentation skills in English Self-driven and strong team spirit Open to fixed-term contract (renewable upon review
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Engineering Medical sciences Mathematics Environmental science Geosciences Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1) Country Australia Application Deadline 14 Jul 2024 - 00:00