224 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:" PhD positions in United Kingdom
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moisture risks, directly affecting children’s health, wellbeing, and learning outcomes. This PhD will develop evidence-based, Passive House–informed retrofit strategies tailored to diverse school typologies
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machine learning and AI research. Strong analytical thinking, problem-solving skills, and the ability to engage with complex data challenges will be greatly valued. Experience with Python or AI frameworks
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committed to decolonising and diversifying Higher Education and fostering a supportive, inclusive, and equitable learning environment. Overseas applicants are welcome; however, the fee waiver covers only
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advancement in electric machine performance. Who we are looking for We seek a motivated candidate with at least a high 2:1 degree in Engineering, Physical Sciences, or a related field. Prior experience (such as
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these programme link learning directly to the working professional. We believe that this philosophy directly fits with the requirements laid down by apprenticeship standards, serving both apprentice and employer
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at leading international conferences and publish in top-tier journals. The successful candidate will gain advanced expertise in multi-sensor fusion, signal processing, machine learning, and positioning
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is offering multiple studentships for candidates from backgrounds spanning the physical and computer sciences. These students will develop core expertise in robotic, digital, chemical and physical
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jointly learn from images and text, most current systems are still limited in three important ways: they primarily rely on statistical pattern recognition rather than structured clinical reasoning
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Project advert Do you want to digitally transform higher education (HE) learning experiences? This novel project aims to combine Artificial Intelligence (AI) and Extended Reality (XR) to create a
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. However, to realise this vision AI systems need specific abilities. One of these abilities is troubleshooting: experiments often go wrong and researchers constantly need to deal with and learn from