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are seeking a Research Fellow in Transport Economics and Big Data Analytics, School of Civil and Environmental Engineering to join School of Civil and Environmental Engineering, Faculty of Engineering. This
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. Sound analytical skills with an ability to communicate complex information clearly both orally and in writing. Demonstrated experience in spatial modelling and/or working with large spatiotemporal data
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of the role The Research Fellow in health data science, will be a research-focused academic position working within the National Perinatal Epidemiology and Statistics Unit (NPESU), a unit of the Centre for Big
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testing, real-world research, and contributing to Australia's defence capabilities, we'd love to hear from you. About the Role You'll be part of a research team focused on large-scale structural testing
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about experimental testing, real-world research, and contributing to Australia’s defence capabilities, we’d love to hear from you. About the Role You’ll be part of a research team focused on large-scale
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to carry out research in the field of plant breeding, phenotyping, crop modelling, GWAS and genome analysis, particularly in cereals Demonstrated capacity to manage and analyse large data sets. Track record
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linked to the microbiome, metabolites and diet. This will include working with large datasets (e.g. proteomics, metabolomics and metagenomics) collected from a pregnancy-birth cohort of children at-risk of
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large data sets or working in applied evaluation projects Experience working with Culturally and Linguistically Diverse communities would be well regarded Demonstrated experience in manuscript and
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metapopulation and/or individual based models Knowledge of Bayesian methods, including Approximate Bayesian Computation Experience with big data analysis and HPC environments Knowledge of additional programming
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an opportunity for a Postdoctoral Fellow. You will contribute to UNSW’s research efforts in developing machine learning and deep learning algorithms for dynamic systems (sequential or time-series data). Experience