Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
are seeking a Ph.D. student to join our multidisciplinary team developing a radical solution for better detection and treatment that uses ultra-thin snake-like robots and advanced optical imaging techniques
-
AI design of ultrathin lenses for compact imaging devices The Faculty of Engineering at the University of Nottingham is seeking an enthusiastic, self-motivated student who enjoys working as part of
-
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
-
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
-
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
-
compressible gas dynamics, heat transfer, free-surface/melt behaviour, and mass transfer driven by phase change, within a GPU-accelerated solver to reduce simulation turnaround times. You will develop and
-
compressible gas dynamics, heat transfer, free-surface/melt behaviour, and mass transfer driven by phase change, within a GPU-accelerated solver to reduce simulation turnaround times. You will develop and
-
on large annotated datasets. Memory-efficient deep learning: Model compression, pruning, quantisation, selective memory replay, and efficient training strategies. Energy-efficient deep learning: Methods
-
(daniel.booth@nottingham.ac.uk ). Team Booth are leaders in the development of advanced cell biology imaging tools and applying them to address important biological questions centred on chromosome biology and
-
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