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to study grid stability, fault propagation, and recovery dynamics. Analyzing control and protection strategies using high-resolution time-domain models. Developing dynamic models for grid-forming and grid
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to recruit a research assistant to develop AI-enabled healthcare applications. Key Responsibilities: Develop and fine-tune computer-vision models, instance segmentation, and retrieval-based estimation from
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project involves interdisciplinary research at the interface of computer science and mathematics, with a focus on bivariate molecular machine learning for modeling molecular interactions and properties
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, physics, materials science, or Civil Engineering. For PhD 1, strong skills in numerical modeling (DEM, Python/C++) and an interest in computational mechanics are expected. For PhD 2, experience in
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multi-physic modelling approach coupling mechanical and electrochemical simulations, it is proposed to bring a novel unified numerical framework in this thesis (i) to simulate the damage in
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numerical tools that the candidate will need to improve. The thesis will also benefits from the experiments in order to validate the proposed model. Profile of the candidate • Master's student in physics
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, an expansion of a novel, data-driven, decision support system for UK dairy farmers, supported by Innovate UK. The core task will be developing, expanding, and automating sophisticated simulation models
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written and spoken English are also mandatory. Meritorious It is meriting to have expertise in one or more of the following subjects: physical modeling, running jobs on super-computing clusters, numerical
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, viscoelastic, and damage-informed formulations) under complex thermo-mechanical loading. Implementing and validating models using computational tools (e.g., numerical solvers, finite element frameworks
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, statistical thermodynamics, and numerical methods for partial differential equations. Experience or a strong interest in the study of stochastic fluid models is required. Knowledge of scientific programming