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, UTS, UWA, Deakin, and Swinburne), and industry leaders such as Ford Australia, Seeing Machines, RACQ, The Department of Transport and Main Roads, National Transport Commission, Transport For NSW, and
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of system and data confidentiality and complete any other requirements. Desirable skills: Experience in programming (C, python, or similar). Knowledge in machine learning or distributed systems. How to apply
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): · Hybrid Multiscale Modelling · Hybrid Physics-Machine Learning Analyses · Coupled Atmosphere-Turbine Models · Uncertainty Quantification in Hybrid Frameworks We offer the opportunity to work in a very
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system for ferry quays, containing labelled damage data as training material for a machine learning model capable of automatically classifying structural damage from drone inspection images. The project
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-NorthWind webpage for more details): · Hybrid Multiscale Modelling · Hybrid Physics-Machine Learning Analyses · Coupled Atmosphere-Turbine Models · Uncertainty Quantification in Hybrid Frameworks We offer
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microfluidic fabrication and experiments 3D printing machine learning. Demonstrated programming skills (Matlab, C++, or Python). Desired Demonstrated ability to work independently and to formulate and tackle
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» Maritime engineering Engineering » Computer engineering Computer science Architecture » Naval architecture Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 23 Aug
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Doctoral Programme Motivation to get proficient in Python Interest in sustainability science and strong incentive to learn Industrial Ecology methods, especially LCA analysis. Proven analytical and
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and strong incentive to learn Industrial Ecology methods like LCA analysis Proven analytical and computational capabilities, in courses and or/thesis deliverables Proven written and oral English
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scientific results, talented PhD students need to acquire knowledge and are also required to exchange knowledge and experience with other PhD students in method-oriented working groups. Supervision by two