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Field
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supervision collaboration in national or international research projects (optional) Requirements: university degree in Computer Science, Computational Linguistics, Mathematics or a related field solid knowledge
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student projects and BSc/MSc theses Your Profile: Master’s degree in physics, electrical/electronic engineering, computer science, mathematics, or a related field Strong background in machine learning
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on the topic assigned for each position. Requirements: outstanding university degree (typically M. Sc.) in Computer Science, Data Science, Statistics, Mathematics or another relevant field study with good GPA
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Infrastructure? No Offer Description Work group: IAS-9 - Materials Data Science and Informatics Area of research: Promotion Job description: Your Job: Join an interdisciplinary team that brings state-of-the-art AI
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degree (or equivalent) in Data Science, Computational Biology, Bioinformatics, Computer Science, Physics or a related field Solid programming skills and knowledge in deep learning, statistical modelling
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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
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: A completed university degree (Master’s or equivalent) with excellent grades in computer science, materials science, physics, or a related discipline Practical experience in data science, including
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tools and concepts. Supervise student projects and BSc/MSc theses. Your Profile: Master’s degree in physics, electrical/electronic engineering, computer science, mathematics, or a related field. Strong
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of software tools and concepts. Supervise student projects and BSc/MSc theses. Your Profile: Master’s degree in physics, electrical/electronic engineering, computer science, mathematics, or a related field
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Our research: Self-Organization in Soft Matter Beyond Amphiphilicity The Research Training Group (in German: Graduiertenkolleg, GRK) RTG2670 “Beyond Amphiphilicity: Self-Organization of Soft Matter Via Multiple Noncovalent Interactions” in the second funding phase at the Martin Luther University...