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for tomagraphic imaging in tissue Neural network correction of distortions in acoustic transducers web page For further details or alternative project arrangements, please contact: alexis.bishop@monash.edu.
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Martin Australia invite applications for a project under this program, exploring the development of Physics Informed Neural Networks (PINNs) for efficient signal modelling in areas such as weather
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that equips and empowers children, adults, families, and communities to understand and intentionally apply the science of wellbeing, intentional practice, trauma, resilience and growth for themselves
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the demographic profiles and contact networks of the individual simulation model will be drawn from Virtual WA: a geospatial analysis platform built in-house by A/Prof Cameron and Camilo Vargas at The Kids. Student
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PhD Scholarship – Modelling the social and political drivers of net zero transitions Job No.: 670767 Location: Clayton campus Employment Type: Full-time Duration: 3.5-year fixed-term appointment
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success for reactions that involve a net gain or loss of electrons: electrochemical reactions. These are an important class of reactions as they can be driven directly by renewable electricity, contributing
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, design, futures or speculative ethnographic methodologies. The proposal should demonstrate an enthusiasm for theoretical research into digital, emerging technology and net zero futures, with reference
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to simulate sewer networks as dynamic systems, targeting ≥90% modelling accuracy. Train an explainable decision-making agent to optimize interventions (e.g., pipe upgrades), balancing cost, equity, and
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of offer for the program if all conditions have been satisfied. Locations Primary location of student: Royal Melbourne Institute of Technology, 124 La Trobe Street, Melbourne VIC 3000 Industry
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English language requirements. Completion of a bachelor (honours) degree or master degree by research in: civil engineering geotechnical engineering petroleum engineering mechanical engineering applied mathematics