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Field
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optimization technologies are revolutionizing the way power grid is operated and planned. CEEESA is seeking talented and motivated researchers to enhance its capability in solving energy challenges using
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Experience in machine-learning modeling for solid mechanics applications Experience in the development and coupling of numerical methods for solid mechanics modeling Experience in digital rock technology
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in clothing manufacture AI and robotics for personalised healthcare, ageing, wellbeing, and transport systems AI and machine learning to enhance efficiency, quality, and sustainability in fashion
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, effective for small-field mini/microbeams, and FLASH-RT. It involves the performance evaluation of the devices and validation in the clinical radiotherapy environment. Developments of computational methods
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Applications are invited for a 2-year position in the field of CFD and modeling of heat pumps at the Department of Mechanical and Production Engineering, Aarhus University, Denmark. Expected start
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Are you interested in green energy, and do you want to contribute to the development of the future technologies for the green transition? At the Department of Biological & Chemical Engineering (BCE
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partners to reduce CO2 emissions in steel production using machine learning. You can find more information here . You will work on a theoretical and an applied project on data-enhanced physical reduced order
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vision, IoT sensors, and blockchain to monitor food quality, safety and animal welfare in real-time and enhance transparency. AI and machine learning will analyse data from pilot sites to identify
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joining a team focused on commercialising innovative technology in the exciting and quickly developing generative AI area. UCC's nasc research centre is within the School of Computer Science
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microscopy, optical interferometry, vacuum technology, finite element method simulations will be involved. Applicants should hold a PhD in Physics, Nano-science, Engineering or similar, experience with optics