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PhD Scholarship Opportunity - Processing intelligence for green metals using in situ X-ray characterisation and machine learning Job No.: 693787 Location: Clayton campus Employment Type: Full-time
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processing and phase transformation. The candidate will work with experimental datasets from techniques such as electron microscopy, EBSD, X-ray diffraction, X-ray imaging and in situ characterisation
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are implemented which detect and correct errors using classical processing known as Decoding. However, decoding must be completed at fast speed and large-scale to ensure errors are fixed before they accumulate. In
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jobs by other users leading to wrong answers. Similar security issues have been detected in the process of quantum error correction or software level compilations. In this project, PhD student will
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strong communication and problem-solving skills and the capacity to conduct independent, quantitative research. They should have either completed, or be in the process of completing, a Bachelors H1 Honours
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principles of the Athena SWAN Charter . This position has a two-stage selection process: Stage 1: Please submit your interest to Professor Muhammad Usman at [email protected] With the EOI please
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, fairness and openness . We fully support the gender equity principles of the Athena SWAN Charter . This position has a two-stage selection process: Stage 1: Please submit your interest to Professor Muhammad
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. Details of eligibility requirements, including English-language proficiency skills, to undertake a PhD in the Faculty of Arts are available at arts.monash.edu/graduate-research/application-process
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protoplanetary discs* Modelling planetesimal collisions during the planet formation process* Example projects in black hole accretion include: Observational appearance of tidal disruption event flares across
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motivation Testing whether the system performs equitably across cultural and language groups Training spans intervention design, trial methodology, human-computer interaction, and applied machine learning