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Approximation. Parameterized Complexity is a vastly growing area within theoretical computer science that allows for the development of exact and approximation algorithms for computationally hard problems by
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integrates machine learning and statistics to improve the efficiency and scalability of statistical algorithms. The project will develop innovative techniques to accelerate computational methods in uncertainty
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Kyropoulou and will work in areas related to (Theoretical) Computer Science, Algorithmic Game Theory, and/or Fair Division with potential applications in Blockchain in the context of the EPSRC funded research
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leverage low-precision accelerators for scientific computing by using a number of tricks, known as "mixed-precision" algorithms. Developing such algorithms is far from trivial. We can look at computational
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PhD Studentship: Accelerating Statistical Algorithms through Machine Learning Award Summary 100% home fees covered, and a minimum tax-free annual living allowance of £19,237 (2024/25 UKRI rate
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This PhD project aims to advance Safe and Sustainable by Design (SSbD) pharmaceutical manufacturing by integrating cutting-edge methodologies, including computer-assisted retrosynthesis, end-to-end
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Short overview of PhD opportunity The PhD studentship aims at studying and developing more comprehensive user interfaces for computer-aided decision-making processes, which can benefit from 3D/360
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formulation, which displays striking similarities to that used by the Computational Fluid Dynamics (CFD) community, has inspired the investigators to adopt conventional CFD algorithms in the novel context
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? Mechanical seals are critical components in high-pressure storage solutions for hydrogen and carbon capture technologies. In this project, you will: Develop a 3D Digital Model: Create an advanced computational
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materials. The computer modelling of LSP remains challenging due to its multi-physics and multi-scale nature. The dependency of the process on the shape of the laser pulse, its energy, ablation layers etc. is