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fundamental and demand-driven research on modelling and analysis of complex social networks. This line of research is broadly focused on modelling, analysis and estimation of complex network models in
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demonstrated application to the surveillance or analysis of internet related crimes. Demonstrated experience in digital tool development, including relational databases, webscraping and webcrawling tools, online
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to an exciting research project on social network analysis and online influence. This position will collaborate with industry partners and academics within the Adelaide Data Science Centre. To be successful you
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roles for transcription factors such as PLZF in sustaining SSC activity and highlighted the importance of growth factor signalling in regulating SSC fate. This position will focus on uncovering
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analytical chemistry, particularly GC-MS analysis of trace volatiles Good communication and problem-solving skills Knowledge in data analytics (python or R) is desirable Knowledge in atmospheric chemistry is
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or knowledge of invertebrates within southern Australian agricultural systems Experience with molecular methods for species identification and/or population genetics. Knowledge of statistical analysis, data
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, with proven experience of contributing substantially to preparation of manuscripts (literature review, analysis, interpretation, writing, submission) Experience contributing to the development
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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