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Exciting Fully Funded PhD: Computational Modelling for High-Pressure, Low-Carbon Storage Technologies. Be a Key Player in Shaping the Future of Clean Energy Storage! School of Mechanical, Aerospace
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to how well they meet the following criteria: A first class or strong upper second-class undergraduate honours degree in Engineering, Mathematics, Computer Science or Physics Excellent English written and
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Engineering, Computer Science or related disciplines. Experience in autonomous system, manufacturing/robotics and machine vision development will be an advantage. To apply please contact the supervisor, Dr Kun
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Aalto University is where science and art meet technology and business. We shape a sustainable future by making research breakthroughs in and across our disciplines, sparking the game changers
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research activities. The applicant will have obtained or be close to obtaining a PhD in Mechanical Engineering or Materials Science. Appointment at Research Associate level is dependent on having a PhD
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Engineering (PhD) Eligibility: UK Students Award value: Home fees and tax-free stipend £20,780 - See advert for details Project Title: Machine Learning and Optimisation-Based Intelligent Substation Design in
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PhD Studentship: Artificial Intelligence for Building Performance – Optimising Low-Pressure Airtightness Testing Supervisors: Dr Christopher Wood (Faculty of Engineering) and Dr Grazziela Figueredo
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We are seeking a highly motivated candidate to undertake a PhD program titled "3D Temperature Field Reconstruction from Local Temperature Monitoring in Directed Energy Deposition." This exciting
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are part of the programme. The research is funded by the Centre of Propulsion and Thermal Engineering at Cranfield University. The work will be conducted at the Cranfield icing wind tunnel (IWT) based
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short courses in the core subjects of this PhD programme including process intensification and green chemistry. This project is part of the Process Industries: Net Zero (PINZ) Centre for Doctoral training