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Do you have passion for sustainable design and development of new materials by combining experiments and modeling? We are looking for motivated candidates for three PhD positions in AI-STEEL Project
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a strong background in computational modeling, optimization, and systems engineering, eager to develop advanced design and simulation frameworks for battery pack topology and e-powertrain integration
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models and reinforcement learning models for 3D graphs of materials to explore vast inorganic chemical spaces and design synthesizable energy materials. You will couple such models with physics simulation
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, and space hardware. This PhD research aims to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust
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, or machine learning is desirable. Familiarity with energy systems or HVAC design is advantageous. Fully-funded studentships (fees and maintenance) are only available for eligible home students in the first
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computing and machine learning—unlocking new possibilities for precision metrology and non-destructive evaluation (NDE) in modern industry and healthcare. This PhD will push the boundaries of next-generation
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, interpretation and writing of grant proposals and publications. To supervise a research team, direct and teach lab practices and to manage lab equipment and supplies. Key Duties & Responsibilities Independently
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Start Date: Between 1 August 2026 and 1 July 2027 Introduction: This project fuses machine learning (ML) based inverse design approaches and topology optimisation (TO) to realise multiscale
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, memory, and energy requirements. The successful candidate will explore novel algorithms and model-design strategies that allow AI systems to operate effectively on edge devices, clinical environments
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, that focuses on Technological Advancement. The goal is to investigate how to evolve advanced, human-centered AI technology to empower human learning, including designing, developing and evaluating systems and