840 engineering-computation-"https:"-"https:"-"https:"-"https:"-"https:"-"Max-Planck-Institutes" positions in Germany
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engineering, computer science or a comparable subject You have good experience in Python You have basic knowledge of the theory and methods in machine learning Good language skills in German and/or English What
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international conferences Supervise student theses Your Profile: Excellent Master`s degree with a strong academic background in computational engineering, mathematics, computer science, physics, engineering or a
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of engineers, microbiologists, and biotechnologists. Our group pioneers biotechnological platforms that connect microbial processes to future industrial applications while uncovering fundamental principles
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integration technologies and transfers them into practical use. Fraunhofer ENAS accompanies customer projects from the idea to the design, technology development, or implementation using existing technologies
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of compact and robust diode laser modules for quantum technology applications, including quantum computers and space-based quantum sensors. For these research activities, we are looking for a Scientific
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Design Technology in Berlin has stood for excellence in production science. We are dedicated to bridging the gap between science and practice in the field of industrial production and offer application
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Description/content The Graduate School Life Science Engineering provides an exceptional interdisciplinary educational programme for highly qualified international scientists and students. Our programme is
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closely with architects, engineers, biologists, and chemists at the University of Stuttgart and the University of Freiburg. The research focuses on the conception, development, and evaluation of bio
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Description Gen-Q is a doctoral training programme set up by Eucor – The European Campus EGTC. In its 2nd call, it provides 8 doctoral positions with an international, interdisciplinary and
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based on machine learning. Reference number 08/26 Your tasks 1. Assessment and analysis of GaN technology characterization data Identification of outliers during testing, with and without machine learning