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of machine learning models, and conformal inference. Applicants should demonstrate scientific creativity, research independence, the capacity to support junior team members, and strong communication skills
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analytical backbone of the programme. It develops sensor-enabled diagnostic cells, multi-modal data pipelines and hybrid physics-informed machine learning approaches to understand interfacial behaviour during
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Machine Learning (OxCSML) research group, with responsibility for leading and carrying out research pertinent to the project, as well as day-to-day management of research activities relevant to the project
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a possible extension for one more year. The starting date is November or December 2025. This post will advance the application of Machine Learning (ML) in weather forecasting and hydrological
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, CPRD) or hospital electronic health records Experience with data linkage and working with routine healthcare data Experience with machine learning or AI applications in healthcare settings Advisory
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of Aberdeen to work on a project “Predicting Response in Triple Negative Breast Cancer Using Machine Learning”. We seek to appoint a creative and motivated individual to use machine learning (ML) to identify
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machine learning, spatial audio and audio-visual AI into groundbreaking creative technology. About you We seek a talented Research Fellow to investigate generative audio AI technology for production
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second in the UK for research power and first in England. About the role The project will be carried out at the Department of Computer Science, in the Machine Intelligence Lab (https
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or machine learning. Excellent programming skills in Python and deep learning frameworks A collaborative mindset and interest in socially impactful research. Experience with sign language data, multimodal
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genetic correlations, development and evaluation of polygenic scores, and integration of genomic predictors into multivariable and machine-learning prediction models for treatment outcome. Working closely