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disciplines: Agriculture Environmental and Related Studies Architecture and Building Creative Arts Education Engineering and Related Technologies Food Health Information Technology Management and Commerce Mixed
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between project workstreams—agronomy, modelling and economics. The successful candidate will undertake both desktop and field activities. Key activities include: Data management, processing, analysis and
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academic and 60 FTE research staff across five academic Disciplines (Applied Chemistry and Environmental Sciences; Biosciences and Food Technology; Geospatial Sciences, Mathematical Sciences; Physics
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Research Centre (CMERC) was established in 2019 to undertake research that works with nature to build an economically and environmentally sustainable future to enrich our coastal communities. From the base
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, operational feasibility, organising and running a workshop with drug-driving enforcement stakeholders, data integration across external sources, and cost-benefit modelling. In addition to the Sub-study 3
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that works with nature to build an economically and environmentally sustainable future to enrich our coastal communities. From the base of CQUniversity’s Gladstone Marina campus, in the industrial port city of
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, Engineering, Environmental Protection, Fine Arts, Genomics, Geophysics, Indigenous Affairs, Mathematics, Population Health, Public Policy, Statistics, Sustainability, Unmanned Aircraft Systems, and Veterinary
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(using beamlines on the Australian Synchrotron); Ion Beam Analysis (using ANSTO’s suite of linear accelerators); Environmental studies using natural radioactivity (including sedimentation rates and erosion
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(43) Computing and information systems (0) Engineering (29) Architecture and built environment (12) Agriculture and environmental studies (16) Health services and support (51) Medicine (51) Nursing (47
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splitting and C–N coupling reactions. Work includes computational modeling of carbon-based materials, conducting simulations to understand reaction mechanisms, and developing and applying machine learning