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Roentgen’s Nobel Prize-winning discovery of X-rays enabled us to non-destructively image inside the body, birthing medical diagnostic imaging and revolutionising materials characterisation
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: The proposed project aims to enhance the sustainability and transparency of the battery materials supply chain by integrating Environmental, Social, and Governance (ESG) criteria and Life Cycle Assessment (LCA
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adaptation is a part of Australia’s emerging climate economy! Join our thriving Geography community in Australia’s largest School of Social Sciences for a PhD project that will contribute to live policy
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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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Curtin University. Candidates should have Masters and bachelor (First Class Honours) degree in Engineering (e.g., Chemical, Materials, Environmental, Resources) or Chemistry (e.g., Inorganic Chemistry
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concept of this project lies in the design of novel perovskite materials as both electrolyte and electrodes for facilitating water splitting for hydrogen production. Such new technology is anticipated
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should have Masters or bachelor (Honors) degree in Engineering (e.g., Chemical, Materials, Environmental, Resources) or Chemistry (e.g., Inorganic Chemistry, Physical Chemistry, Electrochemistry
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) and complete any other CSIRO requirements. Ideally, the applicant will have a bachelor degree in chemistry, chemical engineering, material science or engineering or relevant fields. Preference will be
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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