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in resistance management. Recording, managing and analysing data using established data science methodologies (FAIR, coding workflows, version control). Preparing publications, reports and conference
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environments High proficiency in writing code for data analysis (e.g. using R / Python) and using relevant software Demonstrated capability of writing for publication in high-impact academic journals Excellent
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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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funding Knowledge on a coding language (Phyton, etc) The successful candidate may be required to complete a number of pre-employment checks, including: right to work in Australia, conduct concerning gender
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(e.g., LabArchives, BioRender). Desirable Demonstrated experience in fermentation control, optimisation and scale-up. Experience in the use of electronic lab books Experience in coding languages (Python
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quantitative and analytical skills, with confidence using spreadsheets and/or coding for analysis Experience with process modelling and TEA tools (e.g., SuperPro, discounted-cash-flow modelling, bioprocess
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and optimise code and digital-twinning platforms with industry partners, produce high-quality research outputs and reports, contribute to funding applications, and deliver training workshops and
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reliable – can manage competing priorities, maintain well-structured code and documentation, and meet project timelines. Curiosity and initiative – motivated to learn new methods, improve workflows, and
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or chemistry, or applied mathematics. Demonstrated evidence of computational modelling experience, including code development and data analysis. Ideally experience using one or more of the following: Molecular
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analysis. Adhere to UQ’s Code of Conduct, OH&S and safe handling requirements. About UQ As part of the UQ community, you will have the opportunity to work alongside the brightest minds, who have joined us