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principles, lab measurement, computer vision and ArcGIS, potential fieldwork and UAV flying training. Person specification Experience and/or enthusiastic interest in one or more of the following areas
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change accelerate, we urgently need smart, evidence-based tools to plan, manage, and protect our marine ecosystems. At the forefront of this innovation is machine learning. Its ability to process complex
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combining high-fidelity computational modelling with artificial intelligence to overcome key barriers in performance. The investigation will focus on optimising core gas exchange and combustion processes
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High Performance Computing facility, where the current code is implemented. The candidate will, among other activities, extend the model to treat different management interventions, peat growth and decay
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This is an exciting PhD opportunity to develop innovative AI and computer vision tools to automate the identification and monitoring of UK pollinators from images and videos. Working at
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in AI. Previous publication record in relevant fields: AI, machine learning, computer vision, etc. Previous successful project on a relevant topic. Good knowledge of statistics, probability
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asset records, satellite imagery) with field investigations to identify vulnerable regions and understand surface deterioration processes. You’ll gain experience in spatial analysis, fieldwork, soil and
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using both mono-material and blended fibre systems to meet the mechanical, chemical, and thermal demands of diverse industrial processes. While mono-material felts offer simplified recyclability, blended
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industrial process that underpins not only the supply of consumer goods, but also the scale of food production required to feed the billions of people on this planet. However, catalysis is challenging to study
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) an Evidence Based Surgery Unit and 4) a policy and methods group. The successful applicant will benefit from opportunities for professional and personal development through established collaborations across