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environments like health care and environmental monitoring. This PhD project aims to address these challenges by exploring how evolutionary algorithms and reinforcement learning (RL) techniques can be combined
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environments like health care and environmental monitoring. This PhD project aims to address these challenges by exploring how evolutionary algorithms and reinforcement learning (RL) techniques can be combined
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central question in evolutionary biology and has profound implications for predicting host–pathogen dynamics in changing environments and biodiversity conservation. In this project, you will investigate
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global ecosystems. Archaea are constantly challenged by viruses, which outnumber cellular life by at least tenfold and thus act as powerful evolutionary drivers. Archaea and their viruses are engaged in a
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), evolutionary biology, chemistry (e.g., LC-MS), and microplastic characterisation (e.g., FTIR spectroscopy). They will be supervised by internationally recognised researchers with strong policy and industry links