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modelling and simulation of transmission and distribution networks, including benchmarking data models, developing optimal power flow algorithms, and creating state estimation and multi-energy optimisation
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models. TensorFlow or PyTorch is desirable. How to apply To apply, please ensure you have digital copies of the below information: • Curriculum vitae; encompassing any research presentations and/or
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modelling astrophysical phenomena. The PhD project will focus on developing theoretical methods to generate accurate data to meet this demand. The student will gain expertise in high-performance computational
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PhD scholarship opportunity: Bias in generative AI-driven decision systems Job No.: 680086 Location: Caulfield campus (with possible collaborations at the Clayton campus as needed) Employment Type
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uptake and adherence, and the modelling of future health inequalities by building tools for distributional cost effectiveness analysis. Integrated PhD Program As a candidate in the Centre for Health
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Zhongzheng Wang as your proposed principal supervisor, and copy the link to this scholarship web page into question two of the Financial Details section. About the scholarship Background Two PhD positions
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the closing date if a suitable candidate is identified. For further information For a confidential discussion regarding this position, contact: A/Prof. Robin Hobbs School of Biomedicine E: robin.hobbs
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the closing date if a suitable candidate is identified. For further information For a confidential discussion regarding this position, contact: A/Prof. Robin Hobbs School of Biomedicine E: robin.hobbs
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identified. For further information For a confidential discussion regarding this position, contact: Dr Luke Isbel Group Leader in the Cancer Epigenetics Program at the South Australian immunoGENomics Cancer
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to trick AI-based models, pay little attention to fake-normal data traffic generated by Generative Adversarial Networks (GAN). This PhD research will address a major vulnerability in AI based smart grids by