17 coding-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"CEA-IBS" positions at University of Sydney
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software engineering best practices, including clean, testable code, CI/CD pipelines and GitHub‑based workflows Build and maintain ML and AI pipelines using cloud technologies, with a strong focus on
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of relevant training and experience, experience conducting literature searches, running code, and managing both numeric and sequence data in a research-intensive environment, experience with at least one data
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strong technical troubleshooting skills and the ability to learn unfamiliar systems quickly apply your learning management system (LMS) design experience, with familiarity in basic HTML &/or coding
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on diversity and inclusion . How to apply Applications (including a cover letter, CV, most representative academic publications (up to 3), and any additional supporting documentation such as link to code/other
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requirements of the work area are suitably met maintain the animals within the unit in accordance with animal welfare code of practice and animal ethics committee directives maintain work areas in a clean and
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learning in immersive technologies, UI/UX design, information visualisation, web design, front-end/back-end web technologies, artificial intelligence and/or creative coding, and the ability to contribute
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research databases (including REDCap) demonstrated high-level proficiency in R (or equivalent statistical coding environment) for analysis of large, complex datasets demonstrated experience working with
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: Advanced Python coding skills, including experience building analytical models, automation workflows and production‑ready solutions Hands‑on experience developing AI agents or applied AI/ML solutions Strong
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experience working with coded statistical analysis tools or software packages, such as R a relevant bachelor’s degree, or an equivalent combination of training and experience, suitable for research
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visualization; applicants are encouraged to include links to relevant code or repositories in their CV experience working with multimodal or data‑driven research workflows and translating quantitative outputs