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university research into commercial outcomes. Under this program, PhD students will gain unique skills to focus on impact-driven research. This Project aims to develop a predictive machine learning model
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of the STAMP RSV Program, supported by the Stan Perron Charitable Foundation. The PhD candidate will play an important role in developing models of RSV transmission and vaccination efficacy to inform
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underwater communications is necessary. Conventional approaches in underwater communications only develop fixed models based on human knowledge or understanding which cannot fully cover the highly dynamic and
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submission within a couples therapy. Aims The project will aim to develop and test a model of how couples resolve imbalances along the dominance and submission dimension during couples therapy. Objectives
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publication Strong programming skills and familiarity with machine learning or finite element modelling Not currently receiving another scholarship of equal or higher value Application process Future student
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care. There is evidence that clinical debriefing models can mitigate the psychological effects of these stressful events and improve the psychological safety of their working environment to improve
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responders are at increased risk of poor mental health outcomes. If we achieve similar findings to the university study, this model will reduce suicidal intentions and behaviours in first responders by 42%. It
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results accurately and draw meaningful conclusions to inform further research and process improvements. Background in modelling and simulation using simulation software. Background in Techno-economic
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predictive capability for post-TAVR outcomes against traditional metrics. iii) Incorporate the AI-based frailty evaluation into surgical risk scores for a comprehensive risk prediction. iv) Examine the model's
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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