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analysis, simulation, chemometrics, control engineering, artificial intelligence, soft sensors, and process sensors. We are always looking for new technologies and new methods to monitor and optimize
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well as application optimization. This research focuses on the development of a parallel debugging framework tailored for custom RISC-V instruc-tion set extensions. The goal is to enable efficient execution tracing
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development o Utilization of robotics and microfluidic screening devices o Establishing and kinetic model-based optimization of enzyme cascades o Enzyme immobilization • Scientific and
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Science, or a related field. • Strong expertise in laser optics, with hands-on experience in setting up, operating, and optimizing laser systems • Expertise with Infrared (IR) and Raman spectroscopy is
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) - Semantic 3D Scene Understanding - Face / Body Tracking, 3D Avatars - Non-Linear Optimization - Media Forensics / Fake News Detection How to Apply: Follow the instructions on our application platform: https
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on the design and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization
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on the design and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization
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(MUCCnet: atmosphere.ei.tum.de ) Optimization of an urban sensor network configuration for greenhouse gas and air pollutant measurements using mathematical and physical assessments Analysis of ground-based
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of the research group ‘Crop Physiology’ is to understand the physiology of plants down to the structure and function of genes and proteins. Thereby, relevant mechanisms are identified, which allow optimizing
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efficient for it, maintaining and integrating a zoo of graph data systems is a huge challenge and leaves a lot of room for optimizations. Our vision is to explore opportunities to unify core parts of