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competitive dynamics between cell nuclei and how their interaction leads to emergent organism-scale behaviour. You will perform fluorescence microscopy on nuclei populations and quantify their dynamics while
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spoken English WE OFFER: A young and dynamic team and an exciting work environment A diversity of exciting research questions and possibilities to develop and pursue novel solution approaches Access
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public official employment law in group A14, 100% Lateral leadership of a dynamic and committed team of approx. 10 PhD students Fixed-term full-time position for 3 years with option to extend Innovative
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a strong background in high-performance computing or in numerical analysis. If you think that you have the requirements above, you should apply for this position. We offer a young, dynamic, and
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for research, and #9 in Europe for M.Sc. programs on entrepreneurship. The TUM Campus Heilbronn is a dynamic organization whose goal is to achieve excellence in research, teaching and impact. The
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
of Information-Oriented Control we focus on research and teaching of control and optimization of cooperative, networked, and distributed dynamical systems. We develop novel methods and tools for the analysis and
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the student solutions using machine learning. We offer: - International and gender-balanced group - Dynamic and collaborative work style - Flexible working hours, home office possibilities etc. - Full-time
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in static and dynamic 3D reconstruction, semantic scene understanding, and generative models for photo-realistic image/video synthesis. Overall, the main focus is on high-impact research with the aim
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stimulating environment (TranslaTUM) - a young and dynamic international research group - Further training opportunities - Initial employment contract for 2-3 years with a standard public service salary (TV
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investigate methods that eventually will automate crucial design steps. In addition, we are developing simulators (on various abstraction levels; using, e.g., Computational Fluid Dynamics) which enables us to