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ocean environments, ensure safe and sustainable operations. Our activities are centered on numerical modelling (e.g. CFD, FEA, FSI, optimization, machine learning), but also include experiments and real
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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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develop and improve protein-glycan binding prediction models and use AI, data science, and bioinformatics to identify and design glycan-binding proteins with desired binding specificities. Qualifications
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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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. The workplace The position is located at the Laboratory of Organic Electronics (LOE ), specifically within the Theory and Modelling for Organic Electronics unit in the group led by Associate Professor Glib
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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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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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remote brain areas in vivo in animal models that underlie plasticity in the prefrontal cortex of mice. We will focus on neuronal micro- and macro-circuits that influence our feeding behavior, which