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Field
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using datayvu software and excel preferred Current driver’s license preferred Prior research experience working directly with young children is preferred Work Mode Designation This position has been
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supporting the Net Zero 2050 target. This PhD project will develop an AI-enabled framework that optimizes wind turbine control and predictive maintenance. Using Deep Reinforcement Learning (DRL), the system
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methods in the past. A piece of comprehensive computer software, Pythia with the corresponding capabilities have been developed and tested successfully in several industrial applications. The software can
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labs framework. This studentship will include cohort-based training and activities, enabling students to gain wider skills and develop valuable personal and professional networks. Project Description
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researcher with expertise in communication, project management, and leadership. You will build a robust national and international network and acquire advanced knowledge essential for implementing critical
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define observable events based on expert knowledge and available evidence. Development of a post-race analysis structure, process and data ‘toolkit’ that can build on historical understanding of race
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remuneration package (including 39 days off a year and generous pension schemes). Be part of a diverse, inclusive and collaborative work culture with various staff networks and resources to support your
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microscopy tools such as SEM/EDX, FIB and TEM. Also use dimensional metrology for metal loss evaluation. Thermodynamics calculations using FactSage software will also be used. The candidate will be based
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graduate students and junior researchers on experimental techniques, data acquisition, and data interpretation. Collaborate with PIs to define research directions and work with interdisciplinary teams
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, validate, and refine high-fidelity 3D models of blood flow and vessel geometry using industry-standard CFD software. Analyze simulation results to provide actionable recommendations for design improvements