21 modelling-complexity-geocomputation PhD positions at Curtin University in Australia
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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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complex characteristics of underwater communication channels; the performance of those classical models is poor, since understanding of underwater acoustic channels is insufficient. Recently our research
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, teams are adapting to significant technological advances accompanied by great volumes of incoming data. Such changes have the potential to improve capabilities in complex and uncertain conditions, but
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system (DDS). Based on the existing findings on BBB, develop and optimize DDS for itraconazole delivery. Potential DDS options are liposomes, polymeric nanoparticles, and inclusion complex formation. DDS
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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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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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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
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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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available at the Centre for Optimisation and Decision Science at Curtin University. The research will focus on developing robust adaptive techniques for solving complex problems in mathematical physics