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immunomodulatory factors (de Almeida et al. Sci Immunol 2022, Chao et al. Nat Immunol 2023, Soll et. al Nat Immunol 2024). We use novel cutting-edge technologies in the area of high-dimensional single-cell analysis
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. • Collaborate with project partners. • Contribute to the preparation and analysis of data for publication and presentations. The following qualifications will be of advantage but are not stringently required
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motivated PhD students to strengthen our interactive and collaborative team. The projects are founded on the well-established and highly visible track record of the laboratory in the analysis of plant growth
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tracking T cell tissue entry and exit over time in matched organs by single-cell chimerism analysis. Using multimodal state-of-the-art technologies and specialized high-throughput cell culture methodologies
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analysis (TEA) or an affinity towards these research questions. - Basic knowledge in bioprocess design, bioengineering and/or mathematic modeling - Affinity towards research question in life cycle
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, metal physics, or a similar degree Experience in software engineering (incl. high-throughput computing) Knowledge in the field of materials engineering of metals and materials modelling (i.e. CALPHAD
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-established and highly visible track record of the laboratory in the analysis of plant growth processes regulated by AGC1 kinases. The Chair of Plant Systems Biology has strong expertise in all relevant
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biophysical analysis of smart technolgoes, and will involve collaboration with experimental researchers as well as other modellers. There is another PhD position open at the University of Queensland (Australia
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and simulation tools. Research topics include geometric modeling of engineering products, methods of geometric analysis, methods of Building Information Modeling, modeling and simulation of construction
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, environmental or natural resource economics) or related disciplines strong analytical (i.e. microeconomics, production or resource economics) and methodological skills with a focus on quantitative data analysis