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Field
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modeling and probabilistic machine learning, tackling problems that arise in molecular systems and heterogeneous materials. Eine Postdoktorandenstelle im Bereich physik-informiertes generatives Modellieren
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Information Engineering Machine Learning and Data Science Embedded Systems and hardware-oriented development Modeling and simulation of complex systems Experience with Python, MATLAB, and/or C/C++ Strong
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of the Max Planck Society for the Advancement of Science. The Department of Machine Learning and Systems Biology , headed by Prof. Dr. Karsten Borgwardt, invites applications for a Postdoctoral Research Fellow
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elements. By integrating machine learning, structural optimisation, and automated code-compliance verification, the platform will enable designers to create structural designs based on available reclaimed
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assets include strong programming skills, experience with modern machine-learning techniques such as neural simulation-based inference or transformer architectures, and familiarity with fitting methods and
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researcher in Computer Science, Data Science, Human-Computer Interaction, Psychology, Empirical Educational Research, Learning Sciences, Cognitive Science, or related disciplines who is eager to contribute
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research in the natural, mathematical and computer sciences with a focus on the processing, structuring, and analyzing of large amounts of complex data and the development of computational methods and
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quantitative skills (R, Python, or Stata; experience with machine learning or advanced experimental methods is a plus). ▪ Familiarity with VR-related toolkits (e.g., Unity, Unreal, or eye tracking) is an
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biophysics, computational biology, mathematics in the life sciences, computer science and machine learning with application to biological systems, and related areas. What we seek The ELBE program seeks
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exploration and optimization of the process parameter space, as well as for adaptive, data-driven machine learning approaches to map the electrolysis process to a digital twin. In parallel, data workflows and