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highly collaborative and interdisciplinary research environment, where you'll work alongside experts from fields such as transport and urban planning, engineering, data science, computer science. Skill
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sciences (including meteorology and oceanography), ecology, mathematics, computer science, engineering, economics, or political science. Students who are still working on their Master's thesis are also
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Description The Weierstrass Institute for Applied Analysis and Stochastics (WIAS) is an institute of the Forschungsverbund Berlin e.V. (FVB). The FVB comprises seven non-university research institutes in Berlin which are funded by the federal and state governments. The research institutes belong...
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computer science, bioinformatics or related fields Solid understanding of machine and deep learning and relevant frameworks (e.g. Pytorch or Tensorflow, Keras, scikit-learn, OpenCV) Proficiency in Python, Linux and
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and urban planning, engineering, data science, computer science. Skill Development: Our extensive qualification concept goes beyond research, offering targeted training in research methods, project
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or very good university degree (diploma, master's degree) in transport or related study programs (e.g., civil engineering, industrial engineering, computer science, etc) with a solid foundation in transport
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degree in computational engineering, mechanical engineering, computer science, applied mathematics, physics or a similar area very good programming skills in Python good prior experience with neural
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interdisciplinary research environment, where you'll work alongside experts from fields such as transport and urban planning, engineering, data science, computer science. Skill Development: Our extensive
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Description Within the Collaborative Research Center “Wave phenomena – analysis and numerics” (CRC 1173) we are currently seeking to recruit, as soon as possible, a Doctoral Researcher (f/m/d – 75 %) in Mathematics for the project “Quantized vortices and nonlinear waves” The CRC has been funded...
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welcomes applications from individuals with a master’s degree in the following fields: Computer Science Mathematics Natural or engineering sciences or an equivalent degree, interested in High-Performance