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Field
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is to develop a highly innovative ‘Lab on a Bench (LoB)’ setup, integrated with Machine Learning algorithm, as a high throughput method for screening and developing formulated products that are used in
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specifically addresses the identified challenge by leveraging ML to overcome barriers associated with platform heterogeneity, including differences in resolution, scale, and feature representation. By developing
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and misalignment, facilitating the development and validation of diagnostic and prognostic algorithms. Electronic Prognostics Systems: Facilities equipped to assess the health and predict the remaining
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. Candidates must have a strong motivation for research and excellent programming skills. Expertise of developing computer vision and machine learning algorithms would be desirable, with an interest in image
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This research opportunity invites self-funded PhD candidates to develop advanced deblurring techniques for retinal images using deep learning and variational methods. Retinal images often suffer
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opportunities to address critical challenges in modern society. A shining example of this was the COVID-19 vaccines. Nanotechnology is key to achieving the UN Sustainable Development Goals. As such, key
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prototype/demonstrator of a low-cost smart sensor. To develop an efficient algorithm to process the vibration signals locally and to develop the firmware to be embedded within the sensor node. To validate
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of epigenetic changes to the DNA as biomarkers of biological age. Validation of Biological Age Biomarkers: validate a short-form of the assessments from Phase 2 and develop an AI model and algorithm-driven
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Havoutis Year 1 MSc Course: MSc Robotics Year 2 – 4 PhD Location: Oxford University Research Abstract: This PhD project will focus on developing an AI-based system for multi-collaborative scouting and
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) of high-value critical assets. Through this PhD research, algorithms and tools will be further improved and developed, validated and tested. It is expected that combining the domain knowledge and the