180 programming-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions at Monash University
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combinatorial optimisation, operations research or mixed integer linear programming. An ability to code in C, C++ or Rust is also necessary. Candidates with experience or interest in column generation
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learning. A publication or two in related areas will be a plus. the candidate should have strong Python/R <b>programming</b> skills. The candidate will work closely with experts in both machine learning and public health. Project funding Project based scholarship Learn more about minimum entry...
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collaborators to ascertain how they would like to interact with such a system and then to evaluate the system. Required knowledge Basic programming and knowledge of conversational agents. Learn more about minimum entry requirements .
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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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learning. A publication or two in related areas will be a plus. the candidate should have strong Python/R <b>programming</b> skills. The candidate will work closely with experts in both machine learning and public health. Project funding Project based scholarship Learn more about minimum entry...
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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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collaborators to ascertain how they would like to interact with such a system and then to evaluate the system. Required knowledge Basic programming and knowledge of conversational agents. Learn more about minimum entry requirements .
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. Required knowledge Proficiency in Python Programming, Machine Learning and/or Optimization. Project funding Project based scholarship Learn more about minimum entry requirements .
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like Australia. #sustainability Required knowledge Computer science - programming in C++, Python or equivalent languages. Machine learning, neural networks, classifiers etc. an advantage. Interest (but
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Buffet, and Iadine Chades. "Interpretable Solutions for Stochastic Dynamic Programming." bioRxiv (2024): 2024-08. Wells, Lindsay, and Tomasz Bednarz. "Explainable ai and reinforcement learning—a