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and level C include: A PhD in a related discipline, and/or relevant work experience. Proven commitment to proactively keeping up to date with discipline knowledge and developments. Demonstrated track
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Fellow is responsible for contributing to the advancement of the University's research objectives through focused work on an Australian Research Council funded Research Hub for Carbon Utilisation and
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preparation of peer-reviewed publications relevant to project objectives support occasional teaching activities and contribute to the supervision of undergraduate and postgraduate students. The ARC-funded
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, they will have prior knowledge of infectious disease modelling, Bayesian inference methods and optimisation methods. They will have a developing research profile, with a demonstrated ability to publish
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The Level A Research Fellow is responsible for advancing the University’s research objectives by contributing to a defined project in the field of applied econometrics. This position supports the development
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metapopulation and/or individual based models Knowledge of Bayesian methods, including Approximate Bayesian Computation Experience with big data analysis and HPC environments Knowledge of additional programming
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-technical audiences and engage in stakeholder or end-user consultation. DESIRED CHARACTERISTICS: Demonstrated experience in models of opinion dynamics, Bayesian reasoning models, natural language processing
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(e.g. Xolotl, Centipede), object-kinetic Monte Carlo or similar. Proven commitment to proactively keeping up to date with discipline knowledge and developments. Excellent track record in research (3
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, utilise best practice research methodologies, and participate in project discussions. Actively participate with industry research partners to progress applied outcomes of fundamental research objectives
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codes, finite element or finite different methods, peridynamics, phase field models, multi-objective optimisation methods, CAD. Demonstrated ability to adapt to fast-changing project direction and learn