Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device (SFDI) and also from our custom-built photoplethysmography (PPG) sensor
-
(SFDI) and also from our custom-built photoplethysmography (PPG) sensor. Applicant should have experience in time-series processing with appropriate AI models (recurrent networks, LSTM) and experience in
-
PhD project: Modelling Resilience of Water Distribution Networks Supervised by Rasa Remenyte-Prescott (Faculty of Engineering) Aim: To develop an modelling approach for assessing water network
-
, the University of Nottingham provides the perfect environment to carry out high-impact research that can genuinely shape the UK’s Net Zero future. This is your opportunity to create breakthrough materials
-
the perfect environment to carry out high-impact research that can genuinely shape the UK’s Net Zero future. This is your opportunity to create breakthrough materials for clean energy technologies and develop
-
the University of Nottingham, contributing to cutting edge research into clean and sustainable energy technologies. Vision and Aim Ammonia is an essential component of the global strategy to achieve net-zero
-
Research Group) Aim: Model and analyse component and system level reliability, availability and resilience of hydrogen systems Background Driven by climate change concerns and net-zero carbon targets, in
-
to produce anti-counterfeit markings, dye-free colour images, humidity and chemical sensors, anti-glare coatings and optical filters. This project will develop additive manufacturing of devices with actively
-
including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during their PhD
-
challenging properties of uncertainty, irregularity and mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and