303 structures "https:" "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "Univ" scholarships in United Kingdom
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Field
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with Graphs led by Prof. Nils M. Kriege. Our research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains from
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variety of issues - including bandwidth, size and weight - which preclude their use across many technologically significant applications, such as small/compact, lightweight structures, and complex-shaped
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-driven AI models that capture the underlying process–structure–property relationships governing metal additive manufacturing. By combining mechanistic modelling, in-situ sensing, and machine learning
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an annual stipend of up to £10,000 Supervision and guidance from leading experts in the field Structured research training at SOAS. Access to workspace and resources to attend and present at national
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to elite contexts. Examine how organisational policies, cultures, performance structures, and social relations shape everyday practice and support or constrain high-level performance. Co-develop evidence
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jointly learn from images and text, most current systems are still limited in three important ways: they primarily rely on statistical pattern recognition rather than structured clinical reasoning
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film flow within the microscopic seal gap. Couple CFD with Structural Models: Study the fluid-structure interaction (FSI) and dynamic response of seal rings under real-world conditions. Collaborate with
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semi-structured interviews, surveys, focus groups, analysis of existing data sets, and fieldwork with critical analysis, contributing both to academic debates and to practical understanding
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: Designing and developing CAD models of test coupons and other structures Fabrication of ‘green’ test structures and sintering these across a range of conditions Characterising the mechanical properties
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generation of AI leaders. Through industry exposure and structured cohort activities, you’ll gain the skills and networks needed to shape responsible, high-impact AI development across research, government