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Field
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on ultrafast chirality and attosecond electron dynamics, aiming to develop new methods for probing and controlling chiral light–matter interactions with applications in photonics, biosensing, and materials
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a circular and low-carbon economy. The PhD is expected to cover: Developing dynamic material flow analysis (dMFA) models to quantify steel stocks, flows, scrap generation, and scrap quality across
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develop integrated energy-material scenarios up to the global level and the necessary models. On this basis, potential resource bottlenecks can be identified at an early stage and model-based strategies
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Systems Engineering (ICE-1), our focus is on developing models and algorithms for simulating and optimizing decentralized, integrated energy systems. These systems are characterized by the high spatial and
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student-scholarship holder at the Poznan Doctoral School of Institutes of Polish Academy of Sciences
that will enable the identification of cancer cells experiencing hypoxia. This will allow us to track their fate both in three-dimensional tumor spheroids cultured in vitro and in orthotopic mouse models in
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materials. This PhD project is part of an original research-creation initiative combining engineering, life sciences and design. Its objective is to develop innovative experimental models to investigate
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PhD in Optical Characterization and Photonic Performance Analysis of Liquid Crystal Polymer Coatings
between material development, optical modelling, and prototype integration. Information You will: characterize one-way transparent cholesteric liquid crystal polymer films and switchable photonic coatings
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) designs and/or studies materials with novel properties. This requires expertise in material synthesis, advanced characterization, physical property studies, as well as modeling and theoretical description
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The Materials to Optoelectronic Devices (M2D) group (https://www.m2ngroup.nl
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part of the SSbD framework implementation. • Conducting a comprehensive literature review and data collection on hazard profiles of existing substances/materials and use of computational modelling