21 information-security "https:" "https:" "https:" "https:" "Keele University" scholarships at University of Exeter
Sort by
Refine Your Search
-
The always-on, safety-critical nature of air traffic control raises rich and exciting challenges for machine learning and AI. The University of Exeter in partnership with NATS, the UK’s main air
-
Project Description Chrono-urbanism is an urban planning approach that prioritises time as a core resource, aiming to reduce travel time by placing essential services, leisure, and work within a
-
challenges. Supervisor information: https://experts.exeter.ac.uk/41651-tarje-nissenmeyer https://experts.exeter.ac.uk/41625-george-datseris Ready to bridge mathematical sciences with complex ecosystems and
-
CD3 is a new, multidisciplinary and multi-institutional strategic national research programme dedicated to using data to transform our understanding of cancer risk and enable early interception
-
& Find Out More : To apply for this fully funded PhD Studentship or for more information, follow this link: https://www.exeter.ac.uk/study/funding/award/?id=5840 Application Deadline: 19 APRIL 2026 @ 23.59
-
, addressing engineering questions in how future electricity networks can remain stable and resilient as renewable generation grows. Grid-forming (GFM) control is increasingly recognised as a critical enabling
-
is small but mighty. Working together with Leonardo UK towards immediate real-world applications in an operational environment, you’ll design and create intricate nanoscale geometries and combine
-
regulatory obligations. Hydraulic simulators are physically detailed but computationally slow and calibration-intensive, limiting large-scale scenario exploration and optimisation. Purely data-driven
-
communication is interrupted, such as during disaster recovery, in remote industrial sites, or for temporary large-scale events, fixed infrastructure is either unavailable or easily damaged, creating "blind spots
-
network integration for emerging low-energy opto-electronic AI systems and beyond. The challenge: Machine learning and neural networks are super-charging the complexity of problems that computer algorithms