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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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rooted in process engineering while also addressing the interaction between Power-to-X plants and the electrical grid. You will contribute to interdisciplinary research spanning process engineering, power
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interact to coordinate replication and encapsidation remains unclear. This means that improvements in rAAV manufacturing approaches are mainly empirically driven and incremental at best. In this project
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description A Doctoral Researcher (PhD student) in Machine Learning for Electron–Phonon Interactions and Wannier-Based
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A Doctoral Researcher (PhD student) in Machine Learning for Electron–Phonon Interactions and Wannier-Based Hamiltonians Aalto University is where science and art meet technology and business. We
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tissues. We believe that outstanding science grows from curiosity, creativity and collaboration. Our laboratory provides a supportive and interactive environment where PhD students are encouraged to think
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preserving and innovating the Long Room through state-of-the-art acoustic and digital technologies. By creating immersive and interactive experiences, we aim to foster meaningful connections between visitors
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complexes interact with host ribosomes and translation factors to promote efficient viral gene expression. Using an interdisciplinary approach that combines molecular virology, biochemistry, quantitative
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into different stages of optimization, both as priors and as feedback after optimization outcomes. Information This PhD project is a part of the CoRDS project – Confident Data-Driven Decision Support (https
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. The project is jointly supervised within an ETH collaborative initiative, providing the student with regular interaction with the groups of Prof. Dikopoltsev, Prof. Scalari, Prof. Johnson, and the project