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as required. Demonstrated high level of written and oral communication skills. Preferable Experience in eukaryotic cell culture/tissue culture Expertise with advanced graphing and/or data analysis
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conducting qualitative research, including online content analysis and interviews. Desirable but not mandatory to have experience designing and conducting quantitative research, including survey research
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scripting for simulation and data analysis, along with experience using high-performance computing environments, is required, and experience using structure prediction and/or machine learning methods is
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behaviour during bushfires, including the conduct of online surveys with bushfire survivors to study evacuee transport behaviour and the analysis of quantitative data, involving the development of statistical
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soils and food products, including the traditional food chain. You’ll also play a key role in shaping methods for sample collection, analysis, and data interpretation, working in partnership with local
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experience using Python machine learning and large language models. Experience in machine learning and NLP for automated misinformation detection, social media data scraping and analysis, and human annotation
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research design and qualitative and quantitative data collection and analysis methods 5. Demonstrated experience in industry engagement. 6. Demonstrated experience of research translation and policy
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analysis. Interdisciplinary collaboration. Critical thinking. Qualifications and requirements The candidate should have a PhD in a topic relevant to regeneration and a track record of undertaking and
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this position, you will have: PhD degree in relevant field Demonstrated knowledge of structural analysis of alloy components, Finite Element Modelling (FEM) and preferably morphology/topology optimisation