59 parallel-computing-numerical-methods Fellowship research jobs at The University of Queensland
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for strain engineering in yeast. Conduct microbial cultivation using established fermentation methods and contribute to the development of new fermentation strategies as needed. Coordinate and execute sample
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to contribute to student supervision and research development, as well as service and engagement roles and activities. Key responsibilities will include: Research: Contribute to and develop a research program
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translation, including commercialisation of UQ intellectual property. Develop a coherent research program and an emerging research profile. Supervision and Researcher Development: Contribute to supervision
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these roles, you will be responsible for coordinating the experience testing of interventions, mixed-methods data analysis, and preparation of manuscripts for publication. As research focused academics
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providers and communities, informed by data from other ARC-IFC themes, and guided by relational Indigenous methodologies. Key responsibilities will include: Research: Establish a research program, collaborate
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opportunity to make a significant impact on both fundamental science and emerging applications Key responsibilities will include: Research: Establish a research program, collaborate on research projects, seek
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-term appointment through to 30 June 2027 This position will be directly involved in the delivery of the research projects funded by the NCYSUR through the Australian Government, Drug and Alcohol Program
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, and inclusion, fostering an environment that mirrors our wider community. We're committed to attracting, retaining, and promoting diverse talent. If you require an alternative method to submit your
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. We're committed to attracting, retaining, and promoting diverse talent. If you require an alternative method to submit your application due to accessibility needs or personal circumstances, please contact
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to engage with multidisciplinary teams and external partners. Desirable attributes include experience with spatio-temporal models, machine learning, Bayesian methods, and knowledge of environmental exposure