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electrical engineering, control engineering, computer science, applied mathematics or a related field. The successful candidate will have expertise in at least in one of: Machine learning in the context
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, molecular and mesoscale level particle-based techniques, continuum modeling, statistical approaches and machine learning. The successful candidates are expected to lead an outstanding independent research
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offers education in automation, hydraulics, machine design, product development, mechatronics, robotics, control and systems theory, industrial informatics and production engineering and technology. There
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to apply for our open positions. Benefits In the Materials Informatics Laboratory group, we combine electronic structure simulations and machine learning to pursue innovative applications for future
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, the social dynamics of human-AI collaboration, and advanced machine learning within engineering. Generative AI is fundamentally reshaping how engineers access domain-specific knowledge, interact with
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error correction (advantage) Background in software development (advantage) Optimization techniques and machine learning (advantage) Ability to conduct independent research Excellent written and oral
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to deploy machine learning to support data analytics and complex decision-making processes. Knowledge of modern SW-tools in the area of energy and sustainability is highly beneficial. Your role and goals You
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to bridge preclinical findings with clinical applications. Through advanced computational approaches, machine learning, and AI-driven neuroinformatics, we extract meaningful patterns from omics, imaging
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intelligence in engineering Interest in multi-objective optimization and machine learning Strong background in computational engineering, engineering mathematics and / or computer aided design High
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artifacts. Experience with 3D image data analysis and 3D image visualization. Experience with machine learning or deep learning-based segmentation algorithms. Experience with statistical analysis to interpret