22 coding-"https:"-"FEMTO-ST"-"CSIC"-"P"-"UCL"-"https:" Fellowship positions in Australia
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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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(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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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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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
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immunohistochemistry/microscopy experience (e.g. 3D immunostaining/clearing, 3D confocal/2-photon/light sheet microscopy) multi-omics (RNAseq, proteomics, metabolomics, coding) biomaterials and tissue engineering
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Fellow, you will: Conduct qualitative and quantitative data analysis, including qualitative coding, mixed-methods analysis, and/or network mapping as appropriate. Manage and ensure the ethical handling and
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the Code of Conduct and Values. Cooperate with all health and safety policies and procedures of the university and take all reasonable care to ensure that your actions or omissions do not impact on
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complete Data management for the project including data collection, cleaning, coding, analysis and interpretation of primary/secondary datasets using statistical software packages collaborate and build a