187 data-"https:"-"https:"-"https:"-"https:"-"https:"-"P"-"UCL" Fellowship positions in Australia
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contribution of 17% superannuation applies. Full-time, fixed term position for 13 months. We are seeking a Postdoctoral Research Fellow (Level B) to join the School of Computer and Mathematical Sciences
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design, molecular biology, and data-driven discovery to advance understanding of human retinal disease mechanisms and support the development of new treatments. The role includes undertaking both
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candidate will also be required complete mandatory immunisations. For further information, please view the full appointment booklet . If you are unable to access this link, please email talent@uq.edu.au
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-phenotype-process outcomes. Apply design of experiments (DoE) and statistical modelling for process optimisation. Generate data to support regulatory and translational pathways. Deliver experiment results
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Dr Yee Lian Chew, the successful candidate will play a key role in designing and conducting experiments, analysing data, and preparing manuscripts for publication. This position is part of an ARC
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or chemistry, or applied mathematics. Demonstrated evidence of computational modelling experience, including code development and data analysis. Ideally experience using one or more of the following: Molecular
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demonstrating values-based leadership that supports wellbeing, inclusion, and organisational excellence. This is a research focused position. Further information can be found by viewing UQ’s Criteria for Academic
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to: lead advanced biostatistical and econometric analyses across large and complex health datasets contribute to the team’s publications, grant applications, and scholarly outputs manage and curate data
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. Further information can be found by viewing UQ’s Criteria for Academic Performance . About You Completion of a PhD in sport & exercise sciences, rehabilitation sciences, rehabilitation medicine, public
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requirements of the role and how your skills and experience will ensure your success in the role. Further information is available by contacting Professor Karla Canuto on (07) 4232 1570 or via email to