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Vacancy from 17/04/2025 ∙ Job ID: SMTH-348 The Leibniz Institute for Surface Engineering (IOM) and the Faculty of Mathematics and Computer Science at Leipzig University are seeking to fill the above
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Postdoc (f/m/d): Machine Learning for Materials Modeling / Completed university studies (PhD) in ...
using first-principles simulations software (density functional theory and related codes) # Automated Workflows:Utilize automated workflows on high-performance computing systems for efficient data
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metrology« , we deal with the development of advanced measurement systems for diverse applications in production and life sciences. As part of your thesis, you will perform simulation-based investigations
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. Please indicate in your application which of the above listed projects is most intriguing for you. Your profile Eligible candidates have strong skills in computational molecular (bio)physics, statistical
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characterization and benchmarking protocols for their suitability to provide efficient cost functions for the optimal control of gate calibration in full-stack quantum computers and simulators. Based on your
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systems. In addition, we are dedicated to researching quantum technologies, neuromorphic computing, and the development of 5G/6G technologies. Become part of our team and join us on our research and
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their physical, biological, ecological, and economic determinants, aiding in informed policymaking. Equal opportunity is an important part of our personnel policy. We would therefore strongly encourage qualified
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, computational physics, statistical physics, non-equilibrium quantum many-body physics Ideally, experience with neural quantum states or other applications of machine learning methods in many-body physics
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. Become a part of our team and join us on our journey of research and innovation! What
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The »High-Performance Cutting « department develops technologies and application-oriented solutions for cutting along the entire process chain - from process design and process simulation to real