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Computer Science (EECS) at The University of Queensland (UQ). Key responsibilities will include: Research: Design, build, and characterise optical systems for spatiotemporal beam-shaping. Disseminate
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experience applying these methods to real-world systems and technologies. Familiarity with software tools such as SimaPro, OpenLCA, Aspen Plus, MATLAB/Python, and data visualisation platforms. Demonstrated
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of sensing technology solutions Knowledge of feature engineering and the development of new spectral indices Proficiency in data analysis and visualisation tools using software environments like Python, Google
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variant analysis will be highly regarded (e.g. bulked segregant analysis, mapping population design, whole genome sequencing, long-read sequencing) Experience with R, Python, or equivalent programming
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The University of Queensland, in collaboration with participants QUT, UniSQ and UniQuest. About You Completion of a PhD in cell biology, molecular biology, biotechnology, biochemical engineering, with subsequent
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computational biology Expertise with R, Python, or equivalent programming languages is essential. Passion for making biological discoveries relevant to crop improvement. Strong analytical skills, creativity, and
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. Use coding (e.g., Python, R, MATLAB, or similar) to clean, process, and analyse large MLA datasets and to generate figures, tables, and visual outputs for reports, publications, and presentations
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, next generation industry professionals, state-of-the-art equipment and pilot facilities. FaBA is proudly hosted by The University of Queensland, in collaboration with participants QUT, UniSQ and UniQuest
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of Queensland, Australian National University, University of Western Australia and leading breeding companies, with occasional domestic and international travel. This is a unique opportunity to work at the
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results. High levels of personal integrity, transparency and capability. Experience in crop model coding is desirable. Experience in statistical analysis and data visualisation (e.g. R, Python) is desirable