17 parallel-and-distributed-computing-"Multiple" PhD positions at Loughborough University in United Kingdom
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as early indicators of anthropogenic and climate-driven change. However, limited understanding of the processes shaping species’ biogeographic distributions constrains our ability to predict ecological
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designed to meet multiple needs in marine biodiversity monitoring. The project aims to develop embedded novel deep learning and computer vision algorithms to extend the system’s capabilities to classify
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by detecting and predicting threats such as pests, diseases, and environmental stress in line with the UK Plant Biosecurity Strategy. The project harnesses computer vision, deep learning, and large
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under multiple environmental and socio-economic scenarios. You’ll develop sought-after skills in geospatial analysis, hydrodynamics, sediment transport, machine learning-assisted detection, and hydro
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outlining how you would approach the project, and an up-to-date CV. Under programme name, please select 'Architecture, Building and Civil Engineering'. Please quote reference RAINDROP-CH. Only applicants with
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(computer vision technologies). The interdisciplinary nature of this PhD will require the integration of environmental science, engineering, and community science methodologies. Supervisors: Primary
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, the project accelerates trait data acquisition by applying computer vision to herbarium specimens and field photos, as well as large language models to extract complementary information from literature and
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, please select ‘Loughborough’ and select Programme ‘Mechanical and Manufacturing Engineering’. Please quote the advertised reference number * CSC-26-WS * in your application under the ‘Finance’ section
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Science, Computer Science, Engineering, or an appropriate Master’s degree. English language requirements: Applicants must meet the minimum English language requirements. Further details are available
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University. How to Apply: All applications should be made online via the above ‘Apply’ button. Under programme name, select ‘School of Social Sciences and Humanities’. Please quote the advertised reference