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Your Profile: Master`s degree in physics, mathematics or a similar discipline Knowledge of quantum physics Experience in quantum field theory Numerical simulation skills Ability to show initiative and
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Max Planck Institute for Software Systems • | Kaiserslautern, Rheinland Pfalz | Germany | about 23 hours ago
Computer Science Department at Saarland University. Numerous research topics spanning all of Computer Science are available. Applicants are encouraged to look at covered topics at https://www.cis.mpg.de/ . Course
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associated numerical methods and AI, will be used with High Performance Computing (HPC) to improve understanding of key flow physics and inform future HPT design. Skills and Experience Required: Applicants
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in a variety of lossy media. The project will give you an opportunity to work with theoretical, numerical and experimental aspects of machine learning assisted design of antennas and metasurfaces
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. Experience with isotopic box modeling, numerical simulations, and statistical analysis. Demonstration of effective communication of scientific and technical results (e.g., peer-reviewed publications
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: Algebraic geometry and number theory Area 3: Stochastics and mathematical finance Area 4: Discrete mathematics and optimization Area 5: Discrete geometry Area 6: Numerical mathematics Area 7: Applied analysis
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profound interest in inorganic chemistry, both in experimental and modelling applications. We are looking for candidates who are also interested in the analytical and numerical aspects of the work
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to significantly reduce the turnaround time of SRS, thus enabling their use for industrial design processes. By combining state-of-the-art numerical methods and data-driven modelling techniques, the PhD candidate
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-structure interactions using a combination of high-resolution numerical simulations (CFD) and advanced experimental measurements (Stereoscopic PIV). A dedicated test bench will enable full-scale global
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, this PhD will explore machine-learning (ML) methods to significantly reduce the turnaround time of SRS, thus enabling their use for industrial design processes. By combining state-of-the-art numerical