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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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such that non-credible contingency event impacts can be assessed presents many challenges including: Redispatch of network to reflect future forecast of demand and generation Modelling of future network
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be undertaken in collaboration with Dr Ali Pourmousavi Kani of the School of Electrical and Mechanical Engineering, and Dr Owen Lamont, Lead Software Engineer at OptiGrid. The student will co-located
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. Demonstrated high level of computing skills, including competency with qualitative analysis software (NVivo), spreadsheets and data management systems. Experience in contributing towards producing conference
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Learning (AIML). This PhD project will contribute to the AAGI HDR program where there will be an opportunity to grow your collaborative research within a vibrant network of national and international AAGI
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scholarship. *For the purpose of this award, medical studies is defined as 'the study of the principles and procedures used in preventing, diagnosing, caring for and treating illness, disease and injury in
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sustainability is defined in the broadest possible sense and is open to applicants from any discipline (including but not exclusive to: engineering, law, mathematics, all the sciences, the social sciences and the
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for. Moreover, the areas of applicability and validity of those models are not available. The attempt to define the applicability domains in the 3D Euclidian space of dimensionless capillary-viscous and gravity
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students to study the preconditions influencing the formation of national hydrogen strategies, the mechanisms influencing market adoption of Hydrogen for Net-Zero Initiative ( ) technologies, and the
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sector. Opportunity to strengthen the professional network within the sustainability, AI, and building sectors. Eligibility: The PhD student must be: within the first 18 months of their candidature