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excellent study records in Electrical Engineering, Electronics, Microelectronics, Computer Engineering, or a closely related field, completed by the start of the position Have a solid background in digital
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practical machine learning/artificial intelligence courses and relevant project and thesis experience. You have a keen interest in AI alignment, human-AI interaction, and explainable AI, and enjoy
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the Department of Mechanical Engineering at the School of Engineering and Design (SoED) of the Technical University of Munich (TUM) in Garching, focusing on the design and evaluation of human-machine interactions
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research environment A self-motivated, proactive, and self-driven working attitude Curiosity-driven self-learning ability Written and oral communication skills in Dutch Keep in mind that this describes
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Science, Physics, Mathematics, Robotics, or a related discipline. A strong interest in one or more of the following areas: AI and machine learning, computer vision, signal processing, sensing, robotics, or embedded
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embed user-defined conditions and structural constraints directly into machine learning routines to achieve high-resolution 3D interpolation of rock mass properties. These synthesized geotechnical fields
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alloys for energy applications in harsh environments using additive manufacturing. This research involves integrating computational modeling, machine learning, and experimental investigations to design and
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Degree PhD Learning Sciences (alternatively Dr phil, Dr rer nat, Dr med; not recommended for international students) Course location München Teaching language English Languages Courses are held
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feedback modeling, computer simulation, non-linear model analysis, interactive learning environments and decision-laboratory experiments. Description of the SPARK4B+ project The position is within the EU
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driving simulation, human-machine interaction, physiological and behavioral data collection, AI-enabled systems, and translational safety research across transportation, public health, and national security