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PhD Studentship: Artificial Intelligence for Building Performance – Optimising Low-Pressure Airtightness Testing Supervisors: Dr Christopher Wood (Faculty of Engineering) and Dr Grazziela Figueredo
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of innovative computational methods using Big Data, Behavioural Science and Machine Learning to understand behaviour through the lens of digital footprint/“smart data” datasets, cutting across sectors ranging
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computer science or mechanical engineering. The candidate will have programming experience, particularly on the development of machine learning pipelines. The University actively supports equality, diversity and
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leader in engineering innovation and drive technology, we design and deliver high-performance systems for industrial, automotive, and renewable energy applications. We are now seeking a dynamic Programme
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our most popular modules in the Law & Technology area. We are ideally looking for someone who is able to be hands-on with technology (including robotics) as well as teach the theoretical aspects
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Technology, The University of Nottingham. Applicants are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in on-platform manufacturing engineering. The
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supervisors spans five departments at University of Nottingham including Architecture and Built Environment, Electrical and Electronic Engineering, Mathematics, Physics and Social Sciences. The PhD programme
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Research Group at the Faculty of Engineering which conducts cutting edge research into experimental and computational heat and mass transfer, multiphase flows, thermal management, refrigeration, energy
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immersive technology integration within an educational context. This role is offered as a one-year fixed-term contract. Whilst there is no formal provision for postgraduate studies in medical education, CPD
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Applications are invited for the above post based in the Education Centre. About the role As Professor of Science and Innovation, you will take a senior leadership role as Director of Curriculum