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implementing models that integrate ecological dynamics, species traits, phylogenetic trees, and economic discounting; ● Devising Bayesian or POMDP frameworks to handle uncertainty about species interactions
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close to the nest [1 ] but to better understand foraging, we need landscape level detail. The direction of the project can be tailored, but could include developing and applying Bayesian ML approaches
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health. You will develop and apply cutting-edge machine-learning techniques to identify the most informative indicators of ecosystem change and use them to build dynamic Bayesian network (DBN) ecosystem
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, prior interactions, rank differences, and kin relationships). We will explore the implied cognitive complexity of great ape communication to identify evolutionary trends and simulate dynamics that might
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company. The project has partners from five different EU countries. All, 15 PhD projects are within the overall theme of SiCOI devices and integration for applications in classic and quantum optical
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students at 5 universities and one company. The project has partners from five different EU countries. All, 15 PhD projects are within the overall theme of SiCOI devices and integration for applications in
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survival and growth in naturally regenerating woodland plots subjected to different livestock grazing pressures. Activities include: (i) conducting targeted literature reviews to support the research
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in practice. You will also work alongside a diverse team of researchers and stakeholders from different disciplines and sectors, gaining valuable experience in interdisciplinary collaboration and
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industrial and regulatory partners, ensuring its relevance and applicability in practice. You will also work alongside a diverse team of researchers and stakeholders from different disciplines and sectors
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will be grounded in rigorous mathematics coupled with a sound understanding of the underlying earthworm ecology. Bayesian inference methodologies will be developed to estimate where and when behavioural