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Field
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development of future proposals for funding, into AI for renewable energy. You will consider ways in which the integration of machine learning algorithms might support the wider integration of, and uptake
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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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team. You will lead in the design and implementation of statistical and computational algorithms of different datasets, and implement novel algorithms within the framework of existing code, providing
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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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Experience in devising and developing novel machine learning algorithms Hands on experience with ROS and physical robots Excellent mathematics skills, particularly in areas relevant to robotics and AI
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from motion blur, defocus, and imaging artefacts, which hinder accurate diagnosis. This project aims to restore image clarity by designing intelligent algorithms that recover fine anatomical details
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subjects, including Cyber Security, Programming, Algorithms, Computer Logic and Architecture, Software Engineering, Database Design, both at undergraduate and postgraduate level. Applicants may hold a PhD in
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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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Experience with machine learning algorithms and ideally experience developing novel methods Understanding of basic biological principles and experience interpreting ‘omics data Ability to analyse information