Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ;
- Cranfield University
- ; The University of Manchester
- University of Nottingham
- ; Swansea University
- ; University of Warwick
- ; University of Nottingham
- ; Cranfield University
- ; Newcastle University
- ; University of Birmingham
- ; Brunel University London
- ; University of Oxford
- ; University of Sheffield
- ; University of Southampton
- Imperial College London
- University of Cambridge
- ; Durham University
- ; EPSRC Centre for Doctoral Training in Green Industrial Futures
- ; Loughborough University
- ; Maastricht University
- ; St George's, University of London
- ; The University of Edinburgh
- ; University of Bristol
- ; University of Cambridge
- ; University of East London
- ; University of Portsmouth
- ; University of Reading
- ; University of Surrey
- ; University of Sussex
- AALTO UNIVERSITY
- Harper Adams University
- UNIVERSITY OF EAST LONDON
- University of East London
- University of Sheffield
- 24 more »
- « less
-
Field
-
challenges to the electricity transmission and distribution system, as solar power is not dispatchable and therefore its incorporation as a major element of the generation mix requires the accurate prediction
-
processes. Carbonate biomineralisation is a key process in global carbon cycling, but there are major gaps in our understanding of how biominerals form. We lack a quantitative understanding that can predict
-
challenges to the electricity transmission and distribution system, as solar power is not dispatchable and therefore its incorporation as a major element of the generation mix requires the accurate prediction
-
human behaviour, influenced by people’s social connections, and resources. Predicting disease spread is difficult due to factors like parent’s age, ethnicity, socioeconomic status, and nursery layout
-
predictive maintenance. Gas turbine diagnostics and prognostics has been progressed quickly in recent years and are crucial technologies to predict the health of gas turbine systems and support the predictive
-
predictive accuracy and prohibitively long computational times, making them unsuitable for real-time process control. Artificial intelligence (AI) models present a promising alternative by addressing
-
microbial communities. In this role, you will develop hybrid species distribution models that combine climate and landscape data to predict how microbial taxa niches shift under changing land use and
-
to predict coastal wetland restoration success. Successful candidate will first construct sensors using microcontrollers (e.g., Arduinos and peripheral sensors). These sensors will be designed to measure key
-
of waterlogged conditions, peatlands are projected to be particularly impacted by future climate change, through changes in both temperature and precipitation. Bioclimatic envelope models predict significant loss
-
freshwater fishes, structured around the following objectives: Use the LOC to map the freshwater fish distributions in Madagascar, including threatened, invasive and human food species Create predictive models