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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 validate designs
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simulators (on various abstraction levels using, e.g., Computational Fluid Dynamics) which enables us to verify designs of microfluidic devices even before the first prototype is fabricated. Fabrication: We
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experimental research • Ability to approach work in an analytical, imaginative and structured way, and to work independently in research projects • Good team player and inclination towards acting in networks
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eventual implementation of new design automation methods and software for quantum computing and especially compilation of quantum circuits. Our focus on interdisciplinary partnerships and networks will
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: M.Sc. in Computer Science, Machine Learning, or equivalent with interest in Medical Imaging and Deep Learning. Strong knowledge in Machine/Deep Learning with experience in discriminative models
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Learning in Earth Observation (ML4Earth). AI methods, and especially machine learning (ML) with deep neural networks have replaced traditional data analysis methods in recent years. The Technical University
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-cell data has its own statistical and computational challenges, and standard tools often cannot be applied. The purpose of the position and goal of the project is to develop and apply bioinformatic tools
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research • Ability to approach work in an analytical, imaginative and structured way, and to work independently in research projects • Good team player and inclination towards acting in networks • Very good
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near Munich in Germany. If your goal is to explore novel approaches to advance superconducting quantum computing, we would be happy to receive your application. We are looking for a skilled candidate
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). 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