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, experimentally grounded workflow for rapid microstructure-property optimization in steels. The PhD student will play a central role in this interdisciplinary initiative. They will: Develop and apply machine
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and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) A high motivation and the ability to work independently with a strong team
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the opportunity to contribute to collaborative efforts at the interface of data science, imaging, and materials research. You will strengthen the data science and machine learning activities of the IAS-9 with
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disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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dynamics, data science, and machine learning are beneficial. Please submit your detailed application with the usual documents by August 15, 2025 (stamped arrival date of the university central mail
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of Excellence iFIT Cluster of Excellence Machine Learning Cluster of Excellence TERRA CIN LEAD Graduate School & Research Network Collaborative Research Centers Transregional Collaborative Research Centers (CRC
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PhD Position in Theoretical Algorithms or Graph and Network Visualization - Promotionsstelle (m/w/d)
students with strong theoretical foundations and a desire to contribute to fundamental algorithmic research. Our group works at the intersection of algorithms, machine learning, and interactive visual
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, R) Expertise in machine learning, Bayesian statistics is beneficial Capacity for interdisciplinary teamwork and excellent communication skills Ability to communicate in English fluently
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in physics, electrical/electronic engineering, computer science, mathematics, or a related field Strong background in machine learning, particularly deep learning and optimization methods Excellent