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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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analysis. This role will be pivotal in advancing our ability to measure novel traits in field and controlled environments by implementing current best practices and proposing a program of targeted research
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). Proficiency in numerical modelling, data analysis and instrument control in languages such as Matlab, Python, C/C++, etc. Familiarity with sensor technologies and applications, machine learning, and electronics
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addition to debits, credits can be obtained. The research performed under this internship by an Electrical/Power Engineering or Computer Science PhD student will relate to this reform, specifically investigation
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informed program aimed at better engaging and supporting the education of Aboriginal and Torres Strait Islander students. The collaborative project between several Australian universities, local communities
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computer vision and machine learning research group in Australia -- and contribute to world-leading research projects at the CommBank Centre for Foundational AI This postdoctoral research position is part of
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***Register for the upcoming webinar on 10 June 2025, 10.00am - 11.00am (ACST)*** The John Monash Scholarship enables talented Australians to pursue a master’s or PhD program at any world-class
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opportunity to contribute to cutting-edge research that has a real-world impact on the agricultural sector. The Analytics for the Australian Grain Industry (AAGI) Scholarship Program (AU node) is funded by
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Wildlife Crime Research Hub as part of the ARC Industry Laureate Fellowship program, Combatting Wildlife Crime and Preventing Environmental Harm at one of Australia’s leading research institutions
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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