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Field
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year round Details Research at Sheffield has been developing models of the railway network from a range of perspectives including smart-grid energy consumption, passenger satisfaction, and integration
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-disciplinary research environment Desirable criteria 1. Experience in devising and developing novel machine learning algorithms 2. Hands on experience with ROS and physical robots 3. Excellent
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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
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. You will focus on developing microwave techniques and associated electronics to precisely control the curing process, using AI-based algorithms to optimise outcomes. Full support will be provided
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to apply it in selected poor-resource settings. This project aims to achieve several objectives, including the development of a new AI-algorithm and a paired dataset for comparing how different imaging
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are building out our Platforms & Digitalisation Team - focused on identifying and leveraging best of breed platforms, automation capabilities and developing innovative in-house solutions to further enhance
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: Design and implement models for a knowledge graph as part of an R&D team. Research methods and techniques for populating the knowledge graph. Develop models or algorithms to facilitate risk identification
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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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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