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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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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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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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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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(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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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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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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experimental tasks using Gorilla or other programs that can be used for online tasks. Align with and actively demonstrate the Code of Conduct and Values. Cooperate with all health and safety policies and