108 engineering-computation-"https:"-"https:"-"https:"-"https:" PhD positions in Australia
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should have a strong background in: Data Science, Artificial Intelligence and Machine Learning Python and/or R programming Data preprocessing, feature engineering and statistical analysis Supervised and
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should have a strong background in: Data Science, Artificial Intelligence and Machine Learning Python and/or R programming Data preprocessing, feature engineering and statistical analysis Supervised and
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and Training (VET). Study areas This scholarship is related to the following study areas: Aviation Built Environment and Architecture Business Design Education Engineering Film and Television Health
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following study areas: Aviation Built Environment and Architecture Business Design Education Engineering Film and Television Health Law Nursing Psychology Science Trades and Apprenticeships Games and
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Technology Engineering, or equivalent, excellent mathematical and analytical skills, excellent skills in AI (i.e., deep learning, RL), excellent communication skills (i.e., both written and verbal), the
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translation into routine primary care and community-based preventive programs. Required knowledge Strong skills in mobile app development and full-stack software engineering ML and AI skills Learn more about minimum entry requirements .
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related to the following study areas: Aviation Built Environment and Architecture Business Design Education Engineering Film and Television Health Law Nursing Psychology Science Trades and
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Engineering Film and Television Health Law Nursing Psychology Science Trades and Apprenticeships Games and Animation Media and Communication Information Technology Arts, Humanities and Social Sciences
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, Artificial Intelligence and Machine Learning Python and/or R programming Data preprocessing, feature engineering and statistical analysis Supervised and unsupervised machine-learning techniques Deep
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, Artificial Intelligence and Machine Learning Python and/or R programming Data preprocessing, feature engineering and statistical analysis Supervised and unsupervised machine-learning techniques Deep