Sort by
Refine Your Search
-
satellite SAR, LiDAR and/or optical imagery to enable rapid, safe, and scalable assessments of damage. Candidate methods for temporal modelling and anomalies detection, which are likely to occur at affected
-
retreat cannot be reversed even with rapid CO₂ drawdown. This PhD will identify early signals by the 2030–2050s, targeting specific Antarctic glacier systems that are vulnerable to early retreat (Needell et
-
opportunity to devise an exciting research project, to receive training in data capture and manipulation, statistics, trait analysis, and modelling of interaction webs, and to undertake fieldwork
-
spans animal evolutionary ecology, molecular ecology, and modelling of complex systems, and obtain interdisciplinary training in state-of-the-art approaches and techniques, which are highly south-after by
-
modelled using UK-based case studies, selected from a shortlist in Isle of Portland, S Wales, SW England, and the Peak District. The work will be supported by Deep Digital Cornwall at Camborne School
-
hierarchical models and existing minimum inhibition concentration data (the lowest concentration of an antimicrobial at which microbial growth is inhibited) to refine suggested regulatory targets; Complementary
-
The University of Exeter’s Department of Engineering is inviting applications for a PhD studentship co-funded by the partner Hydro International and University of Exeter Faculty of Environment
-
hydrodynamic modelling to assess anchoring stability, water-level changes, and impacts on energy yield and reliability, in collaboration with Zneco. Year 3 till submission: Electrolyser Integration with Hydrogen
-
in relevant cellular and in vivo models. Depending on progress, it is expected that you will present your research at national and/or international major research conferences. A suitable candidate will
-
an important role in the efficient integration and management of solar energy in modern power systems. The studentship project aims to develop a novel PV forecasting model based on physics-informed neural