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techniques • Explainable AI/ML using visualization • AI/ML-empowered visual analytics of multivariate networks (network embeddings, …) • Large Language Model (LLM)-assisted visual analytics of text, images
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us The High-Energy part of the Theoretical Subatomic Physics group performs research into elementary particle physics from model building and Dark Matter to formal Quantum Field Theory
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compartments including single cell- or bulk sorted immune cells and extracellular vesicles from the lung of the patient cohort, as well as from cell culture model systems. The studies are performed in close
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model building and Dark Matter to formal Quantum Field Theory. Organizationally we are part of the division of Subatomic, High-Energy and Plasma Physics within the Department of Physics . We have a
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in mouse models and cell cultures. Analyze and interpret omics data using bioinformatic pipelines in Python and R. Perform experiments in cell culture and animal models to validate the findings
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mathematics, ecology, history, climatic and medical sciences in collaboration across multiple institutes. An integral part of the project is to develop process-based eco-epidemiological models considering
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sequences, with applications ranging from biogeographical mapping to paleogenetic reconstructions. The candidate will work jointly with Dr. Eran Elhaik to design machine-learning models that unlock
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mathematics as a major: Applied Mathematics program (bachelor's program), Mathematics and Modelling (master's program), and a Master of Science program in Engineering Mathematics. In addition to these programs
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esophageal tissue using a variety of mouse models, organoid co-cultures and spatial sequencing technologies to identify relevant cell-cell interactions. We seek a curious, highly motivated, and creative
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within the Theory and Modelling for Organic Electronics unit in the group led by Associate Professor Glib Baryshnikov . You will have access to the supercomputing resources provided by Linköping