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containerised). Use CFD modelling and lab pilots to optimise hydraulics, mass transfer, and electrode configurations. Energy Integration Quantify full energy balances of MEC operation. Explore integration with
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We are seeking a research assistant with a background in computing to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device
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position (2 + 2 model) under the supervision of Sebastian Szyller. Trustworthy & Adversarial Computing Lab is a newly established group. The lab has an extensive network consisting of companies and academic
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critical, to ensure expected engine performance is achieved. To predict this complex flow and heat transfer, next-generation Computational Fluid Dynamics (CFD) solvers using Large-Eddy Simulation (LES) and
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observations and modelling of the physics and biogeochemistry of Antarctic shelf seas. You will gain experience in computer coding, statistics for environmental science, working with and piloting autonomous
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combining high-fidelity computational modelling with artificial intelligence to overcome key barriers in performance. The investigation will focus on optimising core gas exchange and combustion processes
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, interpretable models from experimental and operational data. The core goal is to balance model accuracy with computational efficiency, while meeting the needs of experimental validation. The framework will
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quantitative data, including spreadsheets, emissions databases, or modelling tool possess strong analytical and communication skills, with the ability to engage and collaborate effectively with both academic
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Thrive Global and two international partners in the United States and Sweden have been funded to deliver a new research programme, titled Collective Action for Race Equity in Health and Social Care (CARE
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will be tasked with the development of new models for the early detection of CIN cancers, applying bleeding edge computational methods and machine learning approaches to improve detection and