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. dos Santos is an Assistant Professor (Lecturer) in Computer Vision at the University of Sheffield. His research interests include remote sensing image processing, computer vision and machine learning
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adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural data to decode multisensory information Investigate how neural
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, antennas, and electromagnetic metasurfaces. The computer-aided simulation of electromagnetic fields is critical in the design of most computing and communications devices, such as high-speed interconnects in
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delivered in routine practice for people with alcohol and drug dependence. This will be a large-scale longitudinal cohort study using national registry data on employment and health. A target trial emulation
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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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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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models, making the use of data-driven approaches a promising direction. This PhD project will investigate the use of data-driven and machine learning approaches, both measurement based but also model based
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from visual and auditory cortices recorded over multiple days Apply and adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural
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for extracting physiological biomarkers from ECG, PPG, and related sensor data Machine learning and AI for predictive modelling and risk stratification Computational physiology modelling to personalise and
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data science and machine learning Additional software skills such as Shiny, LaTeX, Tidyverse, Tableau, C/C++, Java, GitHub Experience in report writing for projects underpinned statistics Attributes and