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Field
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Responsibilities: Lead the design, implementation, and validation of data-driven Digital Twin (DT) models to simulate and forecast dynamic energy demands and renewable generation patterns within shipyard operations
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researchers engaged in a Defense Health Agency project on spatial orientation modeling and disorientation mitigation. The research fellow will participate in generating a report for the Spatial Orientation
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individual to work on an exciting modelling and simulation project, involving extensively applied work at the intersection of software engineering research and modelling and simulation, with real-world testing
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successful applicant will focus on expanding the capacity of the Centre for Water Systems’ existing methodologies and models to simulate urban runoff dynamic and water quality, analyse the propagations
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detection experiments Participate in developing computational models of experiments and performing radiation transport simulations Collaborate with graduate students, student interns, and external
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development of next-generation computational tools for simulating particle-laden two-phase flows by integrating advanced Artificial Intelligence (AI) techniques with traditional computational fluid dynamics
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Melbourne CBD campus About the Role We are seeking a Postdoctoral Research Fellow to join RMIT's Materials Modelling and Simulation group to apply classical Molecular Dynamics and Machine Learning approaches
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conducted in the IWT. Disseminate research through publication in high-quality journals and leading conferences. If possible, develop or adopt numerical simulation models and methods pertinent to icing
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drives, power converters, or real-time embedded controllers. Practical experience in system modelling and simulation tools such as MATLAB/Simulink. Exposure to AI/ML techniques, particularly as applied
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at the RMIT Melbourne CBD campus About the Role We are seeking a Postdoctoral Research Fellow to join RMIT’s Materials Modelling and Simulation group to apply classical Molecular Dynamics and Machine Learning