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/photovoltaic-and-renewable-energy-engineering/our-research/research-activities/characterisation-defects-machine-learning Skills & Experience: A PhD in Computer Science or a related field. Thorough theoretical
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-intensive Schools within the University. The School consists of four discipline groupings: Civil and Environmental Engineering and Surveying; Chemical and Renewable Energy Engineering; Aerospace Systems
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technologies, and integrated (renewable) energy systems to join a net zero transition project, a collaboration between the Rio Tinto Centre for Mine Automation and the Waste Transformation Research Hub
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consists of four discipline groupings: Civil and Environmental Engineering and Surveying; Chemical and Renewable Energy Engineering; Aerospace Systems, Electrical, Computer Systems; Mechanical and
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Catchpole. Applicants should have a relevant PhD in engineering, materials science, chemistry or physics, with experience in perovskite solar cell or perovskite-silicon tandem solar cell fabrication
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response of carbonate and cemented sediments found in Australia to be able to model the next generation of foundations for offshore renewable energy developments. This will involve (i) characterising
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team to undertake applied, industry-focussed research, under the Energy Transmission theme of the ITTC, with a particular focus on PMU based wide-area control to achieve improved grid stability Undertake
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Australian National University | Canberra, Australian Capital Territory | Australia | about 1 month ago
collaboration with other research institutes and industry partners, and are supported through projects funded by the Australian Renewable Energy Agency (ARENA). Applications are particularly invited from
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expertise in aquaculture, marine renewable energy, maritime engineering, environmental assessments and policy and regulation. Through the integration of the knowledge and expertise across these areas
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consumption of electricity. We make sense of the world’s data streaming in from cameras, devices, and sensors. Our expertise in Power Engineering, Renewable Energy Systems, Robotics, AI/Machine Learning