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: Computational materials modeling: DFT, molecular dynamics, phase-field modeling, or multiscale simulations. Data-driven materials discovery: ML models for property prediction, materials design, or synthesis
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, "INFORMED-AI" hub. More details can be found about the INFORMED-AI hub at. The post is fixed term for 24 months with the start data as May 1st , 2026, and the end as April 30th , 2028. The successful
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basis starting from 01/04/2026 for 24 months. For further information, please contact: Prof. Victoria Chapman (victoria.chapman@nottingham.ac.uk ), Dr Federico Dajas-Bailador (F.Dajas-Bailador
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to appoint a highly motivated and experienced postdoctoral research associate in computational materials chemistry. The position is funded by the EPSRC project “Data-driven design of organic mixed conductors
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in candidate multilayered data storage media. The post will include measurement of novel multilayered magnetic materials by a variety of optical measurement techniques. This will include wide field
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if technical problems arise Select, follow, and adapt experimental protocols Gather, analyse, and present scientific data from a variety of sources Contribute to scientific reports and journal articles and the
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diverse team of faculty members, engineers, and industry partners, including renowned researchers at the College of Computing and Data Science (CCDS) at NTU. Technical skills, natural curiosity, versatility
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of Computing and Data Science (CCDS) at NTU. Technical skills, natural curiosity, versatility, and enthusiasm are highly desired traits that will enable success in this fast-paced environment. Key
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and responsibilities Conduct a comprehensive review and synthesis of existing air quality, health and economic data, applying quantitative and computational techniques where appropriate to ensure robust
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information This role is fixed term for 48 months with a proposed start date of 06/04/2026. For an informal discussion about the role please contact Scott Lovell at sdl35@bath.ac.uk. We consider ourselves to be