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essentially new methods to automatically verify cyber-physical systems. Because none of the existing methods and tools for the formal verification of cyber-physical systems are fully automatic, these methods
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(ML4Earth). AI methods, and especially machine learning (ML) with deep neural networks have replaced traditional data analysis methods in recent years. The Technical University of Munich (TUM), together
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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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explore new topics while playing nice in a team. Your main task will be the development, conceptualization, and eventual implementation of new design automation methods and software for your field, e.g
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resonator. You will develop new protocols and hybrid quantum-classical circuits to establish solid state spins as a new electric circuit element. You will employ these circuits as compact magnetic field
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projects in basic biomedical research and who wish to learn methods relevant to their current research. To this end, the grant finances the participation in practical training courses or short-term research
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10.08.2021, Wissenschaftliches Personal Positions in the Formal Methods for Software Reliability group of TU Munich led by Prof. Jan Kretinsky: - postdoc in the area of quantitative verification
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, Li-solid state oxide conductors have almost been neglected as electrolytes to replace classic oxygen conductors in sensors. Your primary tasks include: • Employ different processing methods (including
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responsibilities: - implement, develop and extend methods for processing and analyzing single-cell RNAseq and protein profiles (CyTOF) - develop methods for second level analyses e.g. interaction networks