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in large pre-trained models (vision-language models), generative models (flow matching, diffusion), simulation-based inference, and robust and active learning. The group has a wide network of
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. Simulation-based inference (SBI) addresses this by training neural networks, such as flow-matching generative models, on simulated events. The project aims to develop efficient, robust and calibrated SBI
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up and maintain experimental workflows by implementing or adapting existing tools. Methods will include advanced flow cytometry, in vitro functional assays for hematopoietic stem cells and immune cells
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on leveraging modern heterogeneous computing architectures to enable large-scale, high-fidelity reacting-flow simulations. The models developed at the cell level will subsequently be coupled to module-, pack
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stands are most exposed, but current monitoring relies largely on field inspections and coarse regional assessments that are often too slow or too limited for operational decision-making. The Department
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, that currently consists of 20 individual researchers. The Discrete Mathematics research group is highly active; it holds a weekly seminar, hosts yearly workshops and receives a frequent flow of visitors and
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candidates whose expertise falls within one or more of the following areas: computational and mathematical modeling, statistical modeling, machine learning, network science, bioinformatics, applied mathematics
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. The engineered immune cells are studied using both in vitro and in vivo models and characterized using advanced analytical methods, including multiparameter flow cytometry and high-resolution sequencing
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cutting-edge methods, models and technologies in environmental science, quaternary sciences, bedrock geology, paleontology, physical geography, biodiversity and ecosystem science, remote sensing, Geographic
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model of the human cell. The program is led by Jan Ellenberg, Director of SciLifeLab and Mathias Ulhen, Director of the Human Protein Atlas, together with a collaborative, multi-institutional