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computational skills and experience in R, Python, Jupyter, Notebook, and genetic/genomic tools (e.g., PLINK2, GCTA, MR, FUMA). Experience with big data analytics within Linux and cloud computing environments, and
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criterion, we will consider candidates currently completing a PhD in Economics or a related field (such as Statistics or Applied Data Science) and who have a strong research record and demonstrated research
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criterion, we will consider candidates currently completing a PhD in Economics or a related field (such as Statistics or Applied Data Science) and who have a strong research record and demonstrated research
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. Demonstrated experience using ABS survey data. Experience using large longitudinal datasets such as HILDA or equivalent international datasets (such as BHPS, GSOEP, etc.). Enjoy an outstanding career environment
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. This position will involve the development of data analysis techniques (including machine learning) and process-based algorithms to diagnose and interpret high-frequency hydraulic data for the purpose
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/hardware solutions, preferably in the Agile software development methodology. Experience in large data sets and their platforms/tools, cloud-based architectures, and deployment frameworks for machine