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Field
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. With cutting-edge research, top-tier education, and extensive collaborations, we are a key force in the field. Our core competencies include in vitro ADME models, advanced in vivo methods, computational
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collaborations, we are a key force in the field. Our core competencies include in vitro ADME models, advanced in vivo methods, computational modeling and simulation, as well as patient-focused and policy-related
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. The project offers the opportunity to contribute to state-of-the-art methods in digitalization and intelligent control systems, while collaborating closely with leading industrial and academic partners across
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at the intersection of AI and advanced electron microscopy. The project focuses on developing novel self-supervised and physics-informed deep learning methods to restore and denoise Transmission
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system level where the impact on the entire food system will be analyzed. Of interest are, for example, novel food technologies, but also well-known food processing methods such as for example tofu and
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flow, fluid dynamics, and sustainable energy systems. The research focuses on developing new methods to study and model multiphase flows as key phenomena in energy and industrial processes. The work
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Chemistry (experimental/computational physical chemistry) -Transition metal photocatalysts studied by femtosecond X-ray science with a focus on hybrid experimental/machine-learned structural dynamic analyses
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InfraVis/CIPA, you will have access to both local and national colleagues for stimulating exchanges, discussions, and joint efforts to solve complex challenges, develop new methods, and support research in a
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statistical and algorithmic methods to analyze large amounts of simulation data, models that explain how and why an autonomously controlled machine fails or underperforms, and methods to recognize simulation
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networks (CNNs), which identify local correlations in the images. However, in this project, the aim is to go beyond standard CNN-based methods by developing new approaches based on transformers, and implicit