22 assistant-professor-and-data-visualization PhD positions at University of Nottingham
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An exciting opportunity has arisen for two Research Assistants (RAs) within the Institute of Mental Health. The RAs will be working on the ESRC/NIHR funded DETERMIND programme (www.determind.org.uk
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27 Sep 2025 Job Information Organisation/Company University of Nottingham Research Field Computer science » Other Engineering » Biomedical engineering Medical sciences » Other Researcher Profile
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We are seeking a research assistant with a background in computing to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device
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to the analysis of time series. In particular, the project will examine and develop methods that go beyond the Markovian paradigm. It will consider a range of time series data, focusing on those that show
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, enabling a more stable and efficacious drug delivery over conventionally dosed medicine. This work integrates high data-density reaction/bioanalysis techniques, laboratory automation & robotics and machine
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to co-design these avatars and training experiences. The goal is to create digital tools that help new or incoming carers feel better prepared for the specific behaviours, communication styles, and
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3-year PhD studentship: Scaling-Up Functional 3D Printing of Devices and Structures Supervisors: Professor Richard Hague1 , Professor Chris Tuck1 , Dr Geoffrey Rivers1 (1 Faculty of Engineering) PhD
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motivated PhD student to join our interdisciplinary team to help address critical challenges in high-speed electrical machine design for electrified transportation and power generation. Together, we will make
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’ families, and community organisations to co-design these avatars and training experiences. The goal is to create digital tools that help new or incoming carers feel better prepared for the specific
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in a more accurate analysis of optimizing the service performance. Computer vision approaches such as ones for object identification and action recognition can help to automatically identify deviations