150 computer-science-programming-languages-"Prof"-"Prof" positions at University of Adelaide
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Job no:517208 Work type:Fixed term - Full-time Campus:Adelaide Categories:Level B, Faculty of Sciences, Engineering and Technology Level B ($114,917 to $135,932) per annum plus an employer
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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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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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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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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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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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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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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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% 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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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