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Field
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the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity
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‘Research Area' field blank select ‘PhD Energy Materials' as the programme of study You will then need to provide the following information in the ‘Further Details’ section: a ‘Personal Statement’ (this is a
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-based reviews, data collection and analysis, written outputs, and the dissemination of research findings to different audiences, including through investor briefings and academic publications. We
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considered. Qualifications/Skills PhD degree in a programme relevant to human-computer interaction and/or critical computing, ideally in Computer Science, Industrial Engineering, Interaction Design, or a
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Development of novel processing techniques Modelling techniques that can inform the direction of experimental activity Physical, mechanical and materials characterisation techniques Data-driven approaches
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correction. This machine-learning approach, however, needs a realistic model of light propagation in the retina in order to validate it and to generate the large volumes of training data required. Funding
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mechanisms , smart electroactive materials , embodied intelligence , advanced control systems , and microfabrication techniques . This PhD forms part of the new £14 million VIVO Hub for Enhanced Independent
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at the bottom of the next page after you click “Apply Now”. This document will provide information of what criteria will be assessed at each stage of the recruitment process. Further information We pride
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a team to undertake a PhD in the Optics and Photonics Research Group (OPG), supervised by Dr. Mitchell Kenney alongside collaborators within OPG and Life sciences. (https://www.nottingham.ac.uk
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a team to undertake a PhD in the Optics and Photonics Research Group (OPG), supervised by Dr. Mitchell Kenney alongside collaborators within OPG and Life sciences. (https://www.nottingham.ac.uk