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- AALTO UNIVERSITY
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Start Date: Between 1 August 2026 and 1 July 2027 Introduction: This PhD is aligned with an exciting new multi-centre research programme on parallel mesh generation for advancing cutting-edge high
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Samuelson and her team on a longitudinal study examining children’s performance on multiple word learning tasks at 18-, 24- and 36-months-of age, as well as their vocabulary growth. There will be
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develop AI- and deep learning–based computer vision tools to automatically identify and quantify intertidal organisms. Beyond computer vision, it will leverage machine learning for large-scale, data-driven
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Number of Positions: 1 Eligibility: UK Only Funding: School of Computer Science Scholarship, in support of the EPSRC Grant: Mixed precision in Krylov Methods, providing the award of full academic
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. Experience with numerical methods, finite element method, statistics and machine learning is desirable. How to apply: Stage 1: Submit your 2-page curriculum vitae (CV), transcripts and a 300-word statement
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(computer vision technologies). The interdisciplinary nature of this PhD will require the integration of environmental science, engineering, and community science methodologies. Supervisors: Primary
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This PhD project focuses on advancing computer vision and edge-AI technology for real-time marine monitoring. In collaboration with CEFAS (the Centre for Environment, Fisheries, and Aquaculture
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combining physical models, sensor data, computational methods, and damage and fracture mechanics concepts to create a virtual replica of the composite tank, enabling predictive maintenance, lifetime
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PhD Studentship: LLM-Based Agentic AI: Foundations, Systems & Applications – PhD (University Funded)
of next generation agentic AI systems. In this PhD programme, you will redefine how the world works, learns, and discovers, turning bold ideas into tools used by millions. You will then become one
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Computational background: engineering, physics, maths, or computer science. How to apply: Stage 1: Submit your 2-page curriculum vitae (CV), transcripts and a 300-word statement explaining your motivation