Sort by
Refine Your Search
-
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
-
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
-
are available in the School of Molecular and Life Sciences at Curtin University, Australia. The successful candidates will work with Associate Professor Guohua Jia on his Australian Research Council (ARC) Future
-
, there is an urgent demand for accurate data on ion-beam collisions with atomic and molecular targets for the development and maintenance of fusion reactors, treatment planning in hadron therapy, and
-
Electrochemistry is funded by the Australian Research Council through a Discovery Project entitled “Molecular Engineering of Locally Concentrated Ionic Liquid Electrolytes”. The purpose of this scholarship is to
-
project within an NHMRC-funded program focused on dementia research. Using a systems biology framework, the project will integrate genomic and lifestyle data to identify key molecular pathways and risk
-
the area of microbially induced calcium carbonate precipitation is limited due to poor understanding of bio-mineral reaction kinetics at molecular level; highlighting the need for unpinning the role
-
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
-
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
-
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