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(desirable) Applicants must meet Monash University PhD admission requirements. Scholarship holders must enrol full-time and on campus. Successful applicants are expected to commence by October 2026. Details
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I am interested in the most catastrophic and explosive collisions in the Universe, such as the mergers of neutron stars and black holes. I study these using both gravitational waves and electromagnetic signatures, primarily focussed on linking the data from these exciting experiments with our...
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I am an experimental particle physicist and I specialise in the study of particles containing the beauty and charm quarks. My research aims to help improve our understanding our universe by comparing our experimental observations to predictions made using the Standard Model of Particle...
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: Prospective applicants must hold current registration as a Registered Nurse with AHPRA and satisfy Monash University PhD entry requirements as outlined in the Monash Graduate Research Admission Procedure
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Walters, Indigenous Research Project Manager at Monash University, Indigenous@monash.edu. Applications can be submitted via EOI to Yolande as Research Director of Monash Energy Institute. Other preferred
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to be unconventional. I have projects available within the following research areas (at both Honours or PhD level): "Excitons and excitonic superfluidity in monolayer semiconductors" "Interplay of Dirac
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MD-PhD Industry Leaders Scholarship (for returning MD-PhD students) Industry Leaders Scholarship This scholarship is awarded to Monash University medical students who have demonstrated a commitment
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: $37,145 pa pro rata tax exempt stipend The Opportunity Monash University is offering a fully funded PhD scholarship for a motivated candidate interested in intergenerational play and wellbeing. The project
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Monash University-Pakistan Higher Education Commission (HEC) Joint Scholarship This joint scholarship program enables high-achieving Pakistani students to undertake PhD and research degrees here
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This Masters or PhD project aims to explain the uncertainty of Machine Learning (ML) predictions. To this effect, we must quantify uncertainty, devise algorithms that explain ML predictions and