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-implantation deformations of the devices and their influence on blood flow dynamics. Alongside computationally intensive, fully resolved simulations, the project employs porous media surrogate models and their
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. If you are able to work autonomously and in a team. We offer you: A dynamic research environment and access to state-of-the-art facilities, with a wide range of opportunities for personal and professional
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Postdoc (f/m/d): Machine Learning for Materials Modeling / Completed university studies (PhD) in ...
to collaborative software development and version control systems (Git) # Experience with electronic structure and molecular dynamics simulation codes (VASP, QuantumEspresso, CP2K, LAMMPS) # Motivation to work
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are offering an interesting and challenging field of work as well as an excellent work environment in a dynamic and multinational team, which works closely with national as well as international collaboration
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methods and their implementation, High-Performance Computing experience, methods of Uncertainty Quantification Offer – What you can look forward to: A dynamic, international team from various disciplines
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biodiversity in Earth system dynamics – to serve science and society” Senckenberg stands for curiosity-driven and application-oriented collections-based research. The Department of River Ecologyand Conservation
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states Investigation of non-equilibrium dynamics relating to quantum simulation or pump-probe experiments Machine learning for feedback control of monitored quantum systems Participation in international
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: Dynamical Systems Control Theory Formal Methods Reachability Analysis Computational Geometry Context The applicant will be directly advised by Prof. Matthias Althoff (https://www.ce.cit.tum.de/cps/members
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Cancer Research Center (DKFZ) and the National Center for Tumor Diseases (NCT) Heidelberg. We are a dynamic international group of scientists working together with renowned national and international
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-specific settling velocities, and organic matter characteristics Integrate observational data with physical and biogeochemical models to improve predictions of carbon flux dynamics Collaborate with