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will work on a newly started interdisciplinary project focusing on exploring the AI based generation and use of synthetic data for improving predictions of energy performance of buildings as
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harvesting/storage, and actuators. Many of our projects are based on national and international collaborations including a variety of competences. Prof. Tybrandt is the recipient of the ERC CoG 2022 and
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synthesis (primarily powder-based bulk synthesis) and realize 2D materials through selective etching. The materials will be characterized with respect to structure and composition (XRD, SEM, EDX, XPS, TEM
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electronic systems. Areas of special interest are bioelectronics and neural interfaces, stretchable (semi)conductors, energy harvesting/storage, and actuators. Many of our projects are based on national and
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the problem is explicitly considered. In particular, it will investigate how to tightly integrate state-of-the-art sampling-based methods with state-of-the-art methods from numerical optimal control in a
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in cybersecurity which have led to the creation of many new courses and training forms that are not always based on evidence and didactic principles. Therefore, we need now new knowledge about how we
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within material physics, primarily theory and modelling of atomically laminated materials. We will use open data bases and high-throughput simulations to explore a wide range of known and hypothetical 2D