Sort by
Refine Your Search
-
deep learning algorithms in ESRI ArcGIS or similar software. Desirable Application Proficiency with relevant specialised software and approaches (e.g., geographic information systems, high-performance
-
processes that could be realised in neuromorphic hardware. The research will combine theoretical derivation and simulation-based validation, using mathematical modelling, algorithmic experimentation, and
-
membranes. Your role, based in Sheffield and working with Prof Steve Armes FRS and Prof Graham Leggett, will be to design synthetic pigment-polymer antenna complexes for incorporation into molecular photonic
-
-to-failure dataset is then fed into powerful Artificial Intelligence algorithms, particularly time-series Neural Networks. These models learn the complex sequence of events that reliably precedes performance
-
. Successful re-development for end-of-life composites could enable reuse in other structural applications. This PhD will investigate the development of hierarchical Bayesian algorithms to capture
-
membranes. Your role, based in Sheffield and working with Prof Steve Armes FRS and Prof Graham Leggett, will be to design synthetic pigment-polymer antenna complexes for incorporation into molecular photonic
-
cell-tracking algorithms, we can follow thousands of individual cells in real time as they respond to carefully designed chemical and mechanical cues. These approaches generate uniquely rich datasets
-
, including teeth grinding and normal everyday movements, ensuring the accuracy and reliability of the collected data. Developing, training, and validating state-of-the-art machine learning algorithms
-
interact with the world around us. However, the power requirements and carbon emissions of AI are equally dramatic: training a single state of the art algorithm has the same carbon footprint as the lifecycle
-
, algorithms, and applications’, Information Fusion, 81, 2022. [2] A. Z. Wang et al, ‘Beyond Correlation: Incorporating Counterfactual Guidance to Better Support Exploratory Visual Analysis’, IEEE Trans. Visual