24 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UNIV" "UNIV" "Univ" Fellowship positions at University of Sydney
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Accelerator: https://www.snowmedical.org.au/vision-accelerator The successful candidate will join the Sivyer Laboratory, led by Assoc. Prof. Benjamin Sivyer, which focuses on understanding physiological and
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, Environmental Science (with a quantitative focus) or related fields; strong experience in large-scale data processing and management, including working with high-dimensional, multi-country or time-series datasets
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and experimentally and clinically implement mechanistic and AI based algorithms Support the acquisition and analysis of clinical data, and imaging, software and equipment infrastructure contribute
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informatics proven experience in original research and scholarly activity experience in next-generation sequencing data analysis or integrative analysis of multi-dimensional data high-level skills in
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of all.” The incumbent will be highly experienced in NHMRC research projects and specifically be experienced with large healthcare data sets and possess advanced skills in intensive care research Your key
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recipients and adults aged over 65 · lead and contribute to the development of study protocols, ethics applications, data collection methodologies, and statistical analysis plans for clinical
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that investigate regenerative design and technology in the built environment, including developing indoor environmental quality (IEQ) assessments, undertaking analysis of multidisciplinary data, and applying
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that explore biological and behavioural factors influencing the onset, course, and response to treatment in young people with emerging mental disorders. Extensive collaborations with clinicians, data scientists
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, RedCAP building and record maintenance for secure data entry, and the Clinical trial management system (CTMS). patient data management in accordance with IHC-GCP requirements, the candidate must
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support systems · assist on AI‑enabled clinical decision support projects, including examining how clinicians use AI in real clinical contexts · undertake qualitative and quantitative data