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at seminars and/or scientific meetings Strong written and oral communication skills Advanced computing skills including in programming in R You will bring your strong research expertise to a multi-disciplinary
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activities. The Sydney EarthBank node will join the national AuScope Geochemistry Network , an Australian consortium of Earth Science institutes cooperating to develop national geochemistry research
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of scientific monitoring programs demonstrated experience managing and integrating large datasets experience working in large teams and organising complex field programs a strong commitment to delivering outcomes
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sedimentology, paleoecology, paleoclimatology, numerical modelling, relational database design, and geological data science a strong track record of publications in leading international scientific journals (Q1
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and endothelial dysfunction. The project involves collaborative research with a team of experts in thrombosis, materials science, surface engineering, patient treatment and industry translation. You
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Frontier for Science Program, and will involve collaboration with researchers from different disciplines across four countries. Your key responsibilities will be to: undertake research in metallomics and
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for publication in scientific journals. Present research outcomes at national and international conferences. Collaborate with lab members to contribute to grant proposals and funding applications. Collaboration and
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The School of Medical Sciences is recognised as one of the leading centres for medical science education in the world. With over 100 years of excellence in education, we are proud to be training the next
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to: contribute to an interdisciplinary research program investigating the biochemical properties of a novel enzymatic oxygen sensing system and its role in low oxygen diseases facilitate drug discovery efforts
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-series data interest and experience developing and working with open scientific software interest in analyzing the dynamics of complex physical systems interest in using statistical learning to infer