26 high-performance-computing Fellowship positions at The University of Queensland in Australia
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of Carbon Dioxide (GETCO₂). At our Computational Multiphysics Laboratory (CML), we value innovation, collaboration, and technical excellence. You will benefit from access to large-scale high performance
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internationally recognised for its expertise in computational fluid dynamics (CFD), multiphase and multiphysics flow, and nonlinear solid mechanics, supported by access to world-class high-performance computing
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and cancer immunotherapy. Develop your expertise and research profile working with a high performing team on cutting edge research in state-of-the-art facilities. In this role, you will be expected
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-preservation, and taxonomic analysis. Proficient in purification of natural products using semi-preparative and preparative High Performance Liquid Chromatography (i.e. HPLC). Experienced in operating and
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, electrochemical, digital) into micro/nanofluidic platforms. Perform surface modification, functionalization, and patterning of materials for selective bio-interfacing. Collaborate with interdisciplinary teams
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team to drive innovation in plant breeding. Key responsibilities will include: Research: Conduct and publish high-quality research, develop a coherent research program, and actively pursue competitive
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discipline, including publications in high-quality peer-reviewed journals and presentations at major conferences. Demonstrated high-level mathematical and computer programming skills. Where PhD has been
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of starch-based films and composite films; produce quality research outputs consistent with discipline norms by publishing or exhibiting in high quality outlets; work to support and develop joint research
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project team, produce high-quality research outputs, seek and manage research funding, publish in reputable journals, utilise best practice research methodologies, and participate in project discussions
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technologies that support decarbonisation and clean energy goals. The successful applicant will contribute to the computational modelling and design of Prussian blue analogues, spin-crossover metal-organic