Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
This PhD project focuses on the design and evaluation of hybrid quantum–classical algorithms for large-scale data analytics and optimisation problems. The research will investigate how quantum
-
guarantees of FL. In this project, we aim at an ambitious goal - designing secure and privacy-enhancing algorithms and framework for FL and applying our designs into real-world applications. To achieve
-
package should be prioritised are surprisingly difficult computational tasks. State-of-the-art high-performance algorithms are used to calculate routes for the vehicles in order to minimise costs and
-
This research aims to design a sustainable framework for optimizing distributed computing systems to enhance performance while minimizing energy consumption. Existing scheduling algorithms often
-
abdominal symptoms. Standalone clinical indicators like CA125 or traditional screening algorithms (e.g., ROMA) frequently produce ambiguous results or lack sufficient sensitivity for early detection
-
evolutionary and behavioural game theory, multi-agent reinforcement learning, agent-based simulation, or experiments with people and AI systems. Some students may develop new theory or algorithms; others may use
-
machine learning can be used to understand complex behaviours such as reliability, competence, transparency and trust. The position will design and develop innovative reasoning algorithms and knowledge
-
validate wearable data algorithms, software tools and pipelines supporting large-scale, multi-cohort research. It will contribute to the ProPASS federated data analysis platform, including testing
-
estimation, confidence calibration, model routing, token selection, early exiting, adaptive visual processing, and efficient use of multiple foundation models. The work will combine algorithm development with
-
human-centred embodied AI New methods for modelling human behaviour and interaction dynamics Multimodal temporal and predictive learning algorithms Experimental evaluation against strong contemporary