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the postgraduate research environment. As a PGR at the University of Nottingham you will benefit from training through our Researcher Academy ’s training programme. Based within the Faculty of Engineering you will
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. Programming experience in at least one language such as Python, MATLAB, or C/C++. Strong analytical, quantitative, and problem-solving skills. The ability to work effectively both independently and as part of a
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Numerical methods Programming skills (Python, MATLAB, or similar) Strong analytical and problem-solving skills. Good written and spoken English. Desirable: Experience with photonic/electromagnetics design
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or quantitative data analysis. • Basic computational or programming skills, or a willingness to engage with modelling and data-driven approaches. Strong communication skills, enthusiasm for interdisciplinary
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Area Engineering Location UK Other Closing Date Thursday 30 April 2026 Supervisors: Dr Yaoyao Zheng , Prof. Hao Liu , Dr Omid Saghafifar (Remedium ) Programme Length: Four years Contract Type: Full
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Area Engineering Location UK Other Closing Date Thursday 30 April 2026 Supervisors: Dr Ming Li , Prof. Hao Liu Programme Length: Four years Contract Type: Full-time Prospective Start Date: October
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. (Home applicants only). In this Ph.D. project, you will advance this research field by investigating how to develop, design, and evaluate domain specific multi-agentic AI models and systems that can plan
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of complex behaviours such as void formation and brittleness. In parallel, you will explore formulation and processing strategies to improve toughness, reduce embodied energy and eliminate the need for cold
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, mathematics, or related scientific disciplines. Skills in numerical tools and programming are desirable (MATLAB, python, C++ etc). Any experience or capabilities in engineering design or manufacturing methods
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programming are desirable (MATLAB, python, C++ etc). Any experience or capabilities in engineering design or manufacturing methods would be advantageous. Eligibility and Application Due to funding restrictions