44 assistant-professor-computer-science-data Fellowship positions at Monash University
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and oral communication skills, including drafting of academic papers and grants High level computer skills with software skills such as Microsoft Office, SAS, SPSS If this sounds like you, we highly
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multidisciplinary in nature, cutting across statistics, econometrics, operations research and data science. Specific project outcomes relate to multiobjective optimisation, expected shortfall and conformal inference
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processes, our work leverages big data and systems biology approaches to uncover novel insights into human health and performance. This role offers an exciting opportunity to grow your research profile while
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University's Department of Economics is seeking a Research Fellow to join the project titled “Women in STEM: The Longer-Term Effects of Teachers.” This research initiative aims to understand how teacher
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Professor Gamble in key research initiatives. Responsibilities include ethics applications, conducting literature reviews, recruiting participants, preparing grant submissions, performing data analysis, and
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computational modelling, physics, mathematics and/or scientific programming backgrounds, ideally with experience in Earth System modelling, Earth science or related disciplines. Ideal technical requirements
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questionnaires. The role also supports a range of related research activities including trial coordination, participant follow-up, data management and analysis and preparation of research outputs. This position
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the people who discover them The Opportunity This Research Fellow position sits within a Wellcome-funded initiative focused on evaluating animal models in mental health science and developing a publicly
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of Information Technology is seeking a Level A Research Fellow to join the Department of Data Science and Artificial Intelligence (DSAI). This role offers an exciting opportunity to contribute to cutting-edge research
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implementation science. We are now seeking an exceptional Research Fellow (Level B or C) to lead innovative methodological research in statistical theory for adaptive variants of longitudinal cluster randomised