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, aiming to explore and develop AI algorithms, frameworks, and hardware architectures for efficient edge deployment in vehicles, with a focus on neuromorphic computing. You will be part of the scientific TUM
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of distributed computing, machine learning, image and text analysis, randomized data structures, high-performance computing, and quantum algorithms. Beyond this research, we aim to support computational thinking
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and Objectives Industry Objectives: Develop methods and algorithms for robust real-time 3D situational awareness and semantic 3D environmental segmentation. Create algorithms and representations
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energy use more efficient. We develop new optimization methods, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity
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, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a sustainable
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, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a sustainable
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, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a sustainable
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processing workflows including QC and reproducibility metrics * APIs and packages supporting the development of new algorithms spanning large * language modeling of DNA and RNA sequences, and algorithms
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storage Innovation in the Machine Learning algorithms for EDA in terms of Computational Complexity, Performance Scores, etc. To learn more about our previous work, please check out our website
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for various technologies and develop algorithms and software tools dedicated to accelerating research on multiple levels. We are working at the intersection of computer science, physics, and material science to