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microstructure in materials. A distinctive element of the project is its data-driven approach. Together with colleagues at Saxion University of Applied Sciences, you will contribute to the development of machine
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with dislocations and how hydrogen modifies these interactions Develop a DFT-accurate machine-learned interatomic potential (MLIP) for a multi-component Fe alloy system, enabling predictive molecular
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embrittlement (HE) in circular steels, with a particular focus on the role of tramp elements at experimentally informed microstructural features. You will combine first-principles modelling and machine-learning
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manufacturing approaches, investigating melt behaviour, densification, defect formation, and microstructure in materials. A distinctive element of the project is its data-driven approach. Together with colleagues
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, increasing steel circularity introduces microstructural complexity through tramp elements, precipitates, inclusions and segregation phenomena. While considerable progress has been made in understanding
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embrittlement is one of the major barriers to the safe deployment of hydrogen technologies. At the same time, increasing steel circularity introduces microstructural complexity through tramp elements
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Car tires are very important and complex parts with high safety and reliability requirements, responsible for maintaining the contact between a vehicle and the road. Tires are subject to wear due to
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during film growth, and how the films respond to external perturbations, such as molecular guests, light or charge. The focus will be on organic cages and metal–organic framework (MOF) thin films as key
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circuits. Building on preliminary results for resistive circuits, you will study circuits containing memristive and capacitive elements, as well as more general dissipative networks. The project combines
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Effect of Tramp Elements effect of tramp elements in martensitic stainless steels Job