389 machine-learning "https:" "https:" "https:" "UCL" "UCL" positions at Monash University
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problem-solving capability High computer literacy, including proficiency with Microsoft Office Substantial relevant skills and experience An understanding of the University environment and its dynamic
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postgraduate qualification in Data Science / Computer Science (PhD preferred) Strong expertise in Python and/or R, SQL, data engineering and machine learning Experience with EMR systems (Cerner highly desirable
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Environmental Engineering Mechanical and Aerospace Engineering Electrical and Computer Systems Engineering Chemical and Biological Engineering Materials Science and Engineering About the Role We are seeking
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they fulfil the criteria for Masters by Research & PhD admission at Monash University. Details of the relevant requirements are available at https://www.monash.edu/engineering/future-students/graduate-research
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requirements are available at https://www.monash.edu/engineering/future-students/graduate-research/how-to-apply Your application will be looked upon favourably if you: Graduated in the top 10% of your year level
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Time series are an ever growing form of data, generated by numerous types of sensors and automated processes. However, machine learning and deep learning methods for analysing time series are much
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information about behavioural patterns, but scoring this manually is time consuming. For this reason, machine learning solutions have been developed to automate behavioural prediction [5-12]. DeepLabCut [5] is
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Excellent written and verbal communication skills Analytical thinking and problem-solving capabilities High-level computer literacy and attention to detail Knowledge of the university research environment and
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. Wallace", Computer Journal, Vol. 51, No. 5 (Sept. 2008) [Christopher Stewart WALLACE (1933-2004) memorial special issue [and front cover and back cover]], pp523-560 (and here). www.doi.org: 10.1093/comjnl
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to real-life data. The goal is to generate new knowledge in the field of time series anomaly detection [1,2] through the invention of methods that effectively learn to generalise patterns of normal from