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: Development of machine learning algorithms for the localisation of seismic sources (e.g., on 2D grid maps) Analysis and preprocessing of large DAS datasets Use of synthetic training data from seismic
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should be implemented to speed-up the acquisition rate and to optimize the setup sensibility and efficiency. Then implementation of new algorithms to build new biomarker maps should be also developed
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situated in the field of machine learning. Potential research topics include, but are not limited to, algorithmic knowledge discovery, graph mining and social network analysis, optimization for machine
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of this role is to support and contribute to an industry innovation research project. The Research Engineer will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep
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increasingly shapes biomedical research and healthcare decision-making, we also value candidates who can help students critically understand how algorithmic systems affect equity, access, bias, and real-world
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The opportunity The University of Liverpool is a key partner in a £14 million initiative (https://tinyurl.com/yc5z768m ) to develop a sustainable, next-generation manufacturing facility, using
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. This field encompasses Computer Science, Data Science, Artificial Intelligence, and related interdisciplinary areas, with a focus on computing technologies, software development, algorithm design, and
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applicant will work with the ReXIl team, AIML, and 4DMedical to turn data into clinical impact. They will be responsible for developing algorithms for image analysis, creating predictive models for disease
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computer science, such as Data Structures, Algorithms, Computer Architecture, Operating Systems, Databases, Computer networks, Cloud Computing, Machine Learning, Data Science, full stack Web Development. Prior
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will be to develop novel or improve existing AI algorithms and conduct investigations aimed at improving our understanding of the evolution and function of microbiomes. You will be responsible