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institution of TUM Campus Heilbronn that uses data to answer relevant questions and solve real-world problems. It brings together fundamental, methodologically driven research in optimization, machine learning
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learning, safety-critical control, probabilistic modeling, verification, or optimization; Excellent communication skills in English and the ability to work both independently and collaboratively in
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of workflows in Python to optimize throughput, reproducibility, and data management. The overarching goal is to create a standardized and scalable platform that accel-erates discovery in stem cell biology and
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—such as engine load, fuel flow, and environmental conditions—to optimize combustion and propulsion strategies. This dynamic adjustment ensures that hydrogen, with its unique properties like high flame speed
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ranges. • Design and optimize HSI data-processing workflows, including spectral calibration, preprocessing, classification, and mapping. • Integrate HSI with complementary spectroscopic techniques (Macro
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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Computer Science or Mathematics, ideally with a background in one or more of the following areas: Optimization, Game Theory, Machine Learning Applicants must demonstrate: • An excellent academic record, including
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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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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 methods, machine learning
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: 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 and satellite-based