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; they make sense to humans and are accessible to algorithmic techniques while neural models are adaptive and learnable. The aim of this project is to develop models which combine these advantages. The project
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secondment is to the group of Prof. Kemerink at the University of Heidelberg, Germany, for the simulation and identification of organic p-n junction doping structures for efficient emission. The second
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diversity, and therefore particularly encourages women and those outside the gender binary to apply for the position. For additional information, please contact Assoc. Prof. Johanna Björklund (johanna
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questions include automated modeling and model simplification/refinement supported by generative AI, system identification, and 3D reconstruction algorithms. Additionally, the research involves developing
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organic pollutants are taken up, distributed, metabolized, and excreted in zebrafish. We have a particular interest in critical developmental stages, including early development and juvenile stages