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models Uncertainty estimation and calibration Failure and out-of-distribution detection Adaptive and selective computation Model routing and dynamic inference Generalisation to unseen environments Embodied
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Centre for Health Economics, Monash Business School, Integrated PhD Program 2027 Fully Funded 4.5-Year PhD in Health Economics - Monash University (Melbourne, Australia) Job no.: 625101 Location
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package should be prioritised are surprisingly difficult computational tasks. State-of-the-art high-performance algorithms are used to calculate routes for the vehicles in order to minimise costs and
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cooperating with each other, but in many cases competing for individual gains. This structure may not always work for the benefit of science. The purpose of this project is to use game theory and computational
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Background and Motivation Modern deep learning models have achieved remarkable success in computer vision and natural language processing. However, they typically produce overconfident predictions
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Focus The PhD candidate will undertake research including: Experimental characterisation of aerosol generation, plume structure, droplet-size distribution, velocity fields and entrainment in a jet
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federated learning and multimodal deep learning models for healthcare. The project will focus on enabling privacy-preserving learning from distributed healthcare data sources, including longitudinal medical
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, and multimodal deep learning approaches that enable privacy-preserving learning across distributed healthcare data sources Support health outcomes with research in transformative applications in
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research at leading international conferences. Indicative total stipend: approximately $54,280+ per annum (tax-free), plus up to $13,265 in travel support and access toEmotiv neurotechnology, computing and
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, stakeholder engagement, and strategic uplift. You are comfortable operating in complex environments, leading distributed teams, and driving clarity and performance in high-pressure situations. You will bring