-
Methods In this project we want to provide a better understanding of how cloudiness affects, and is affected by, environmental factors called “cloud controlling factors”. Success of this goal will be
-
PhD Studentship in Aeronautics: How offshore wind farms and clouds interact: Maximising performance with scientific machine learning (AE0078) Start: Between 1 August 2026 and 1 July 2027
-
revealed that blowing snow over sea ice can generate fine sea-salt aerosols, which warm the surface by modifying cloud properties. We propose that other impurities deposited in Arctic snow, e.g. black carbon
-
real-time coordination among aerial systems, ground infrastructure, and cloud services. Ultimately, this project aims to redefine the role of aerial systems in urban society—not only improving logistics
-
and ecosystems) and fine particles (again, harmful to health, and impacting climate through scattering of radiation and influencing cloud formation). There are two key uncertainties in BVOC emissions
-
cloud data centres. However, this can come at the cost of performance and slower function processing, which manifests as higher energy consumption and increased operational costs (OpEx) for operators. So
-
, mobile platforms, industrial sensors/cameras, GPU workstations, and cloud platforms. Training covers research methods, scientific writing, open-source best practices, and impact/engagement. You’ll be
-
engineering, or atmospheric science* Expertise in and passion for computational modelling and software development/engineering Expertise in cloud physics or contrails preferred but not required Creative problem
-
). The Computer Science group is looking for students to work on one of the following projects Distributed Intelligence for Self-Organising Cloud–Edge Infrastructures Carbon-Conscious Resource Scheduling for AI Workloads
-
system stems from the need to increase efficiency in marine monitoring. Furthermore, existing computer vision solutions often depend on cloud computing infrastructure and require specialized expertise. A