72 computer-science-intern "https:" "https:" "https:" "https:" "UCL" research jobs at University of Nottingham
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the applications of Machine Learning. Dr. Anthony Bellotti is Professor in the Department of Computer Science at UNNC. He received his PhD in machine learning from Royal Holloway, University of London
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is looking for ambitious, talented academics with a passion for teaching as well as research flair to join its team of science and engineering experts. UNNC is part of the University of Nottingham’s
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working with Johnson Matthey, but aligned with the EPSRC funded Programme Grant “Dialling up performance for on demand manufacturing” (EPSRC reference: EP/W017032/1). Our vision is to create a toolkit and
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Applications are invited to join an ERC-funded research programme in the laboratory of Dr Vinay Shukla. The position is part of the project BreathingUnderground, which explores how oxygen
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existing team. The School is committed to creating opportunities for people traditionally under-represented in Mathematical Sciences and strives to maintain an environment where people can be their
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background in computer vision and strong understanding of a range of AI methods. They must hold a PhD in computer science, with a focus on developing AI-based computer vision approaches. Expertise can be
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they may need to further develop (and for which we will provide support). The applicant will also be expected to work side-by-side with staff recruited in computer science and the wider academic team
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to conduct comparisons of their economic, technical and environmental performance. It is expected that the work will lead to publication and/or contribute to the dissemination at national/international
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, Health Sciences or a related field and have experience of qualitative research methodologies and techniques, as well as excellent written and interpersonal skills. Experience of research with vulnerable
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to understand plant performance and climate feedback mechanisms in the Middle Jurassic. The project will use an experimental framework, to link plant morphology and chemistry to measurements of ecophysiological