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of economically valuable species and invasive species that may compete with economically valuable species or promote wildfire. Learning Objectives: The postdoctoral fellow will have the opportunity to apply
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and supervision of postgraduate research students. To develop research objectives and proposals for own or joint research including research funding proposals To attend and or present at conferences
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integrate sophisticated AI systems, rigorously testing, validating, and tracking learning models, and troubleshooting issues to ensure system accuracy and reliability. A core objective of this role is to
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techniques. The incumbent is expected to exercise sound judgment in selecting and applying appropriate methods and techniques to achieve research objectives, working independently within broadly defined
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the team’s work across its different content areas. We are seeking a candidate with strong quantitative and statistical modeling skills, particularly in Bayesian methods, who is ready to advance their career
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of rail with wider city and regional transport networks. A focus of this work is the application of optimisation techniques (e.g. evolutionary algorithms, or Bayesian techniques) to identify high performing
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methods, Bayesian statistics, and/or an interest in applied empirical problems. We are particularly interested in candidates with expertise in applications of artificial intelligence in marketing
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activities and course delivery materials to support course objectives, advise students, work collaboratively to identify instructors, and perform service to the unit, university, and profession
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of economically valuable species and invasive species that may compete with economically valuable species or promote wildfire. Learning Objectives: The postdoctoral fellow will have the opportunity to apply
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modern clinical trial design, such as Bayesian Adaptive Clinical trial design or established expertise in statistical methods such as structural equation modeling, causal data analysis. Experience in