12 coding-"https:"-"FEMTO-ST"-"L2CM"-"Inserm"-"https:" research jobs at The University of Queensland
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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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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
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representatives. Analyse and code empirical data using project-specific frameworks. Contribute to research publications and dissemination in high-impact outlets. Support knowledge translation and engagement with
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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
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clinical AI evaluation. Develop code framework, proof of concept (MIMIC database), integrate with EMR-connected solution, and support NASCENT rollout at Townsville University Hospital and other sites
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to adapt argumentation, tone, and structure to meet diverse editorial and institutional standards. You will need to demonstrate the capacity to “code-shift” between research, policy, and practitioner