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not fully capture the high-temperature, complex thermal-fluid interactions within the pebble-bed. This PhD project will focus on advancing porous media models for pebble-bed HTGRs by leveraging newly
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aims to develop a novel theoretical framework for nonlinear and robust control of dynamical systems from a phase perspective. You will have the opportunity to freely explore multiple research directions
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providing a structured, semantic framework that enhances knowledge sharing and data reuse across different platforms and systems. Project Aim This PhD will develop an ontology-based methodology to improve
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will dynamically adjust turbine parameters such as yaw, pitch, and torque to maximize Annual Energy Production (AEP) while minimizing component stress. Additionally, a hybrid predictive maintenance model
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to understand these dynamics. This project proposes a novel pipeline of ideas to generate tools and techniques to simulate HIV infection dynamics using a multiscale agent-based modelling technique (cells, viruses
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is characterised by complex and highly dynamic turbulent flows that define the performance and design of renewable energy systems and their infrastructure. This PhD project aims to enhance
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opportunity for a motivated scientist to unpick the impact of host factors on tumour structure. To lead this research as a doctoral student you will be passionate about using large-scale data to address
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, multidisciplinary PhD research projects across areas such as: Zero Emission Technologies. Ultra Efficient Aircraft, Propulsion, Aerodynamics, Structures and Systems. Aerospace Materials, Manufacturing, and Life Cycle
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exploiting the structure of inputs and doing a multivariate complexity analysis. The goal of this project is to develop more efficient parameterized approximation algorithms and preprocessing algorithms (also
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Supervisors: Dr Lukasz Figiel, Warwick Manufacturing Group, Dr Ferran Brosa Planella, Maths Project Partner: Jaguar Land Rover Efficient batteries for automotive industry are critical for achieving