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[Malaysia Campus- VPSSP] An AI-Informed Planetary Health Framework for Equitable AMR Risk Mitigation
modelling from Project 1, we will conduct focus groups and interviews with communities in high- and low-risk zones to capture local knowledge, behaviours, and risk perceptions related to AMR. In parallel
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programming Funding reference https://www.monash.edu/study/fees-scholarships/scholarships/find-a-scholarship/monash-graduate-scholarship-mgs Learn more about minimum entry requirements .
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programming Funding reference https://www.monash.edu/study/fees-scholarships/scholarships/find-a-scholarship/monash-graduate-scholarship-mgs Learn more about minimum entry requirements .
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publications, citations or scientific careers to test the implications of a model. References Fortunato, S. et al. “Science of science.” Science 359 (2018): eaao0185. https://doi.org/10.1126
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publications, citations or scientific careers to test the implications of a model. References Fortunato, S. et al. “Science of science.” Science 359 (2018): eaao0185. https://doi.org/10.1126
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programming background with fundamentals in machine learning and data science. Experience in building visualisations and interactive immersive environments (using game engines like Unity3D) is
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machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch or TensorFlow) Project funding Other Funding
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] “Empirical Agent Based Models of Cooperation in Public Goods Games | Proceedings of the Fourteenth ACM Conference on Electronic Commerce.” Accessed September 10, 2021. https://dl-acm
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] “Empirical Agent Based Models of Cooperation in Public Goods Games | Proceedings of the Fourteenth ACM Conference on Electronic Commerce.” Accessed September 10, 2021. https://dl-acm
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from an unbiased strategy space.” Journal of the Royal Society Interface 16 (2019): 20190127. https://doi.org/10.1098/rsif.2019.0127 Perera, I., de Nijs, F. and García, J. “Learning to cooperate against