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that are critical of generative artificial intelligence will not be disadvantaged in the selection process, but must still meet all other requirements. The below themes are offered as inspiration for research
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reimagined economic outcomes must be measured in novel ways Focusing on three critical sectors – energy, transport and water – and three key processes – standardising climate information, underwriting climate
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Location: Turning Point, 110 Church Street, Richmond Employment Type: Full-time Duration: 3-year fixed-term appointment Remuneration: There are various scholarships offered by Monash University to support
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English-language proficiency skills, to undertake a PhD in the Faculty of Arts are available at https://arts.monash.edu/graduate-research/application-process/ . Applicants should ensure they familiarise themselves
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of eligibility requirements, including English-language proficiency skills, to undertake a PhD in the Faculty of Arts are available at https://arts.monash.edu/graduate-research/application-process . Applicants
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of eligibility requirements, including English-language proficiency skills, to undertake a PhD in the Faculty of Arts are available at https://arts.monash.edu/graduate-research/application-process/ . Applicants
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Graphs/ AI methods to this domain. This position has a two-stage selection process: Stage 1: Please submit an EOI using the Faculty of Information Technology Research Project Enquiry form here
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conversion of biomass into high-value platform chemicals and bio-slurry fuels. The project builds on our patented and published bench-scale work, aiming to scale up the process to continuous operation using
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, addressing critical challenges in the transition to sustainable metallurgical processes. The successful candidate will develop a fundamental scientific framework to tackle key research questions in
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supergiant stars right before the explosion Searching different astrophysical channels that produce r-process elements Connecting the properties of long-duration gamma-ray bursts and associated supernovae web