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, causing poor rates of asymmetric redox reactions or poor ability to detect chiral analytes. Chirality is as powerful as it is elusive: we do not have accurate models to explain and predict, especially
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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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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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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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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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on animal models of glioblastoma to evaluate the effectiveness of the selected DDS in tumour growth inhibition, survival rate, biocompatibility and brain targeting efficiency. Aims • Develop a novel and
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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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for ADHD emphasise core symptom clusters comprised of (1) inattention and (2) hyperactivity/impulsivity, various conceptual models of ADHD also highlight a prominent role for deficits in emotion regulation
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symptoms. Alexithymia is a major focus of our lab's research, whereby we have created new theoretical models of alexithymia (the attention-appraisal model of alexithymia; Preece et al., 2017), new
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Characterization Techniques Study the advanced electrochemical characterization methods. Gain deep insights into the reaction models associated with PCFCs. 3) Understanding of Electrocatalytic Performance and