159 computer-science-programming-languages-"the"-"IDAEA-CSIC"-"RAEGE-Az" positions at University of Adelaide
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PhD in Computer Science, Engineering or other Machine Learning-related field. • Programming experience in python, C++ or other relevant language and experience in deep neural networks • Strong
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and fertiliser. The incumbent will be involved extensively in the AgriFutures Program of Research on “Insects for food, feed and fertilisers”, including running various experiments and performing data
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software used to test and evaluate telescope performance during commissioning. The position will also require a strong commitment to developing an innovative research program in high-energy gamma-ray
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methods. Strong experience with scientific computing and data analysis, ideally using python or an equivalent language. A strong record of producing peer reviewed research-based publications in areas
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hardware and software applications, including competency across the full Microsoft office suite of programs. Excellent interpersonal communication skills including the ability to effectively communicate with
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Office skills. Skills in data manipulation tools and/or programming languages such as Cognos, Power BI/Power Query, PySpark, SQL and R Desirable: Experience with data integration and ETL tools such as
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% superannuation applies. Fixed term, full time position for 24 months. This position is based within the University of Adelaide’s barley research program, located in the School of Agriculture, Food and Wine (Waite
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knowledge of health economics, but this is not a requirement as training will be available throughout the PhD program. Stipend: The scholarship will be for 3.5 years and has a stipend of $35,300 (indexed
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to contribute to continuous improvement initiatives by identifying service enhancements and assisting with program and procedure development project support, events, and broader University initiatives to ensure
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conducts field surveys and sampling across a national network of over 900 one-hectare plots, to collect soil and vegetation specimens and data. The TERN Ecosystem Surveillance field program enables