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programming languages such as C and Python Proficiency in deep learning frameworks such as Pytorch and Tensorflow Knowledge in imaging and computing device and equipment Good written and oral
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Responsibilities Development of new machine learning modeling approaches Development of new advanced control and optimization algorithms Optimization of carbon capture process operation Provide regular project
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requirements: PhD Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field, obtained within the last five year Research Experience in one or more of the following
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applications (e.g. Microsoft Office, data management and online meeting tools) would be required as well. In addition, the role will require the following job relevant experience or attributes: Keen interest in
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knowledge related to acoustic modelling (e.g., COMSOL Multiphysics) and measurement. Demonstrated data analytic skills, ideally with machine learning. • Other general requirements: Demonstrated ability
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modelling, noise mapping and measurement. Demonstrated data analytic skills, ideally with machine learning. Other general requirements: Demonstrated ability to undertake high quality academic research with
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are demonstrated knowledge related to acoustic modelling, measurement and soundscape. o Essential are demonstrated data analytic skills, ideally with machine learning or statistical modelling • Other general
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Responsibilities: Conduct programming and software development for data management. Design and implement machine learning models for optimizing data management. Conduct experiments and evaluations of the designed
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computer programming to verify the efficiency of the designed solution algorithms Analyze data acquired from the field survey Develop machine learning models for prediction and recommendation Job
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resilient (urban) model for other cities to learn – in an increasingly precarious environment of climate change and (un)sustainable practices. Secondly, this project will explore how Singapore also learns