46 computational-physics-superconductor PhD positions at University of Nottingham in United Kingdom
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Applications are invited to undertake a PhD programme, in partnership with Airbus, to address key challenges in ensuring adoption of sustainable approaches to fuel additives for aviation use
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covers tuition fees, a stipend, and RTSG (research training and support grant). Alongside the scientific PhD training, the programme will provide a wide range of training opportunities. DTP Standard
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supervisors spans five departments at University of Nottingham including Architecture and Built Environment, Electrical and Electronic Engineering, Mathematics, Physics and Social Sciences. The PhD programme
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(School of Computer Science) External Partner: Build Test Solutions Ltd (BTS) Start Date: 1st October 2025 Eligibility: Home students only | Minimum 2:1 in a relevant discipline Stipend: Home students only
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of real-time digital twin (physical or Artificial Intelligent based) of electric propulsion system including propulsion motors, power converters, fuel cell and batteries etc within the real-time simulation
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considering various elements in the process. The integration of computer vision techniques in this project will also enhance the value of this work. The students will not only gain an experience and insight
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research programme funded by the Academy of Medical Sciences Springboard award. This project aims to explore the role of these neighbouring glycoproteins in neurotrophin-mediated neuronal development as
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supercritical water systems to generate samples that will help optimise a process that will then be scaled into pilot and large scale pilot systems with partners in the consortium. Aim This project will focus
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the foundation of computer vision, monitoring, and control solutions. However, real applications of AI have typically been demonstrated under highly controlled conditions. Battery assembly processes can be
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explore or optimise the flexible structures and manufacturing process of Litz wires. This studentship offers the opportunity for the PhD student to lead the development of innovative simulation tools