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of the complex physics governing the interaction between the heat source and the material. Additionally, it seeks to develop an efficient modelling approach to accurately predict and control the temperature field
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environment. Join us in shaping the future! The position is part of Profi 8 research “Transformation of urban systems” funded by the Research Council of Finland. The work aims at modeling carbon flows
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sources such as (i) atmospheric models, (ii) satellite remote sensing, (iii) land use information, and (iv) meteorological data. The aim of this PhD is to develop and implement models for integrating data
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) offer new avenues to tackle this problem. AI models have demonstrated strong potential in clinically relevant insights from electrical signals such as ECGs, and from cardiac imaging modalities including
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around three core scientific pillars—regenerative medicine, biomaterial science, and translational research models—SHIELD supports research on therapeutic strategies, novel antimicrobial materials, and
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be testing and optimising predictive models for use in realistic healthcare settings. This studentship will suit a student interested in working in health data science, particularly with an interest in
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remain largely unexplored. This research will be carried out by using the world-leading research facilities (high temperature experiment, advanced characterisation and modelling) at the Advanced Steel
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) offer new avenues to tackle this problem. AI models have demonstrated strong potential in clinically relevant insights from electrical signals such as ECGs, and from cardiac imaging modalities including
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verification methodology and corresponding toolchain to detect and mitigate such threats to CPS at the design time making the CPS resilient-by-design. Typically, CPS are modelled as hybrid systems, comprising
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: Computational Modelling: Employing simulation tools (e.g., GEANT4, light transport) to explore novel metamaterial designs, predict performance, and optimise key parameters such as timing resolution, light yield