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partially observable Markov decision processes (POMDPs). Methods in Ecology and Evolution , 12 (11), 2058-2072.
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to the programmer to quickly resolve type errors and support there understanding and propagation of types throughout their program.
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postdoctoral researchers and PhD candidates, and building strong partnerships across academic, clinical, and community sectors. You contribute to strategic planning, foster research excellence, and help drive
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Levin Kuhlmann Research area Machine Learning We are seeking a highly motivated and innovative PhD student interested in exploring the opportunities for using AI to enhance personalisation of services and
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accounting software, advance level of using Microsoft Office suite of applications such as Power BI and Power query as well as Excel modelling, utilisation of web technology and experience in the use
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judgment. Advanced digital literacy and experience with governance software tools. If you’re ready to make an impact in a role that combines strategic thinking, operational excellence, and stakeholder
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limits of generative AI, computational science, and cross-disciplinary innovation. This role suits someone who excels at the intersection of software engineering, high-performance computing, and applied
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of policy conditions. The fellowship project is based on critical theories from fields like political economy and STS, alongside qualitative methods including document analysis and ethnography. Proposals
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, providing opportunities for creating rich contextual environments without having to conduct site visits. This PhD project aims to leverage innovative spatial computing technologies and proposes Immersive
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-route tasks to maintain uninterrupted service. This research area involves developing fault-tolerant systems that adapt to hardware and software failures. Students will work on predictive maintenance and