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socioeconomic impacts of artificial intelligence (AI), gender bias in algorithms, critical analyses of fintech, dynamics of platformisation, the emergence of digitally enabled forced labour, biometrics and
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fields of communication science such as public sphere and public opinion research, journalism and political communication through the use of innovative, computerized tools and algorithms for collecting
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programmes. The Computer Science programme is focused on software engineering, with modules in Software Engineering, Software Project Management, Data Structures and Algorithms and Data Base Systems. The
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Machine Learning for both supervised and unsupervised algorithms. Deep understanding of principles and best practice in machine learning, with a focus on NLP especially in sequence labelling tasks based
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of rail with wider city and regional transport networks. A focus of this work is the application of optimisation techniques (e.g. evolutionary algorithms, or Bayesian techniques) to identify high performing
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approaches, sound art, algorithmic governance, media and cultural studies, digital media, environmental approaches, and others. The communities and physical research sites of the project are located in
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at the University of Sheffield within the consortium is to lead nationally the development of quantum machine learning (QML) algorithms. The research will involve designing innovative QML approaches and collaborating
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diabetes and prediabetes by analysing voice patterns, providing a non-invasive and innovative method for early diagnosis. Specifically, this project will develop novel deep learning algorithms, and audio and
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participate in developing algorithms for tau lepton identification, and will also have the opportunity to assist with silicon module construction for the ATLAS tracker upgrade. Instructions for applying can be
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publications is a plus. Experience in designing, developing, and implementing computer vision models and algorithms. Proficiency in Python and its standard coding practices and common libraries. Experience with