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; Software Systems & Cybersecurity; and Human-Centred Computing - with cross-cutting research themes covering work from core computing science through software engineering to social and organisational
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, reduce resource waste, and create scalable mental health interventions, advancing national sustainability and education priorities. Value • Stipend of AUD $47,020 • Maximum period of tenure of an award is
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is pioneering the development of a SaaS platform based at LotFourteen that leverages AI to help homeowners find the best balance in design and material selection for building resilient homes
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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-based materials,[ 3 - 11] non-Cu metals and alloys,[ 12 - 16] and molecular catalysts such as cobalt phthalocyanines.[ 17 - 20] Despite these scientific breakthroughs, most current electrolysis systems
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the areas of experimental and theoretical physics, synthetic, physical and computational chemistry, material sciences and related areas. The Opportunity The OPTEXC IRTG involves 20 academics in Australia and
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required new IEC standards relevant to the performance and lifetime of printed solar technology through developing a detailed understanding of printed solar degradation mechanisms and interactions with
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) and computer simulation (FEA) Experience in material characterisation and experimental testings Knowledge in impact dynamics Passionate and have interest in pursuing PhD degree. Experience in research
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, Materials Science, or Manufacturing Engineering. Applicants should also ensure they meet the eligibility criteria for entry into a Swinburne PhD program. Full details can be found here . Additionally