Sort by
Refine Your Search
-
dispersal may also represent a significant introduction route for insects. This project aims to develop and apply quantitative methods to assess wind-borne dispersal risk for a range of pests of concern to GB
-
programme that will train the next-generation of doctoral carbon champions who are renowned for research excellence and interdisciplinary systemic thinking for Net Zero. The ReNU+ vision is that they will
-
. Developing recommendations on how insights from routine datasets can inform scalable decision‑support tools. Additional data collection. You will embed patient and public involvement throughout and join a
-
systems with "self-diagnosis" and "self-healing" capabilities. By integrating federated learning, graph neural networks, and blockchain technology, we will develop a framework that moves beyond static
-
biology approaches to develop rapid, low-cost, and field-deployable tests for detecting quarantine pests/pathogens. You will evaluate technologies such as CRISPR-based systems, strand displacement reactions
-
have implications for food security and conversation. The successful student will explore innovative synthetic biology approaches to develop rapid, low-cost, and field-deployable tests for detecting
-
sequencing technologies (such as nanopore sequencing) has enabled the discovery and analysis of complex regions of the genome for the first time. Novel long read sequencing approaches developed in the Ryan
-
stormwater) are a sustainable solution, but their long-term performance often suffers due to generic design approaches that overlook plant ecology and the interaction with soil structure development. This PhD
-
approaches that overlook plant ecology and the interaction with soil structure development. This PhD project will transform rain garden design by linking plant traits to hydrological and ecological outcomes
-
and optimization but lack frameworks to continuously verify AI safety in operational contexts. This project aims to develop a dynamic validation framework for AI systems using high-fidelity digital