16 parallel-computing-numerical-methods Postdoctoral positions at Chalmers University of Technology in sweden
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)* Strong background in computational mechanics and numerical methods Demonstrated experience with LS-DYNA or comparable commercial FEA software Proficiency in Python programming for scientific computing and
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Kahl (Computer Vision, Chalmers), Kathlén Kohn (Algebraic Geometry, KTH), and Mårten Björkman (Robotics, Perception and Learning, KTH). The research focuses on developing novel machine learning methods
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of quantum computers, and resource theory for quantum computation. They will carry theoretical studies using both analytical and numerical tools, in these subject areas. They will also interact with
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We invite applications for several postdoctoral research positions in experimental quantum computing with superconducting circuits. You will work in the stimulating research environment
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different mixing and reactive properties compared to conventional fuels. In this project, turbulent mixing and combustion of hydrogen in air will be studied through optical experiments and numerical modelling
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-scale computational methods, and bioinformatics. The division is also expanding in the area of data science and machine learning. Our department continuously strives to be an attractive employer. Equality
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fundamental questions about the particles and forces governing our Universe to energy-related research. The methods of our investigations are also diverse and complementary, and range from theory and computer
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(AIMLeNS) lab is a tight-knit team of computer scientists, chemists, physicists, and mathematicians working collaboratively. Our focus is on developing practical methods that blend traditional disciplines
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Chalmers University of Technology focused on the recycling of carbon fibre composites. The project aims to develop a novel method for recovering fibres using magnetic fields, with the goal of lowering
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and calibration of reports from various sources. Collect and analyse large-scale cross-industry accident data using FRAM (Functional Resonance Analysis Method) within LLMs to identify human-, technical