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members. ● Conduct training sessions on statistical methods, programming, and analytical tools as needed. Quality Assurance: ● Ensure adherence to best practices in data quality, code review
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across the study team including: overseeing data transfer agreements between institutions; version-controlling and archiving code and leading data cleaning, harmonisation and analysis. Throughout
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. • Reviews participants medical records, collects and codes surveys, and verifies active status for participants. • Attends relevant meetings, and provides detailed written and verbal reports on participant
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relevant PhD or equivalent qualification/experience in a related field of study, and will have experience in the coding and development of RShiny apps. The successful applicant will be a nationally
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and deploy advanced deep learning and foundation models for surgical scene understanding segmentation, tracking, and operator assistance. You will write, test, and optimise Python and C++ code for real
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the University and with external collaborators. Support project coordination activities, including documentation of research workflows, version control of code and data, and supervision or mentoring of research
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, principles and theories. Develops tools and code to conduct advanced analyses of ocean and atmosphere datasets. Adheres to University and unit-level policies and procedures and safeguards University assets
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coding knowledge as these are transferrable to R. The candidate will be working with the Principal Investigator(s) on the analysis of national health datasets, utilising an array of methods to infer
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Torres Strait Islander people, and people of all abilities, cultures, sexual orientation, and genders. Pre-employment safety and suitability checks: In accordance with the National Higher Education Code
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and robustness across varying noise conditions. Familiarity with PAM workflows and tools and/or marine bioacoustics is required. Strong Python skills, ability to document code and workflows, and