48 molecular-dynamics-simulation Postdoctoral positions at Chalmers University of Technology
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We are seeking a postdoc to co-design efficient and realistic simulation algorithms for noisy quantum circuits in superconducting hardware, combining quantum modeling with hardware-aware performance
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methodologies for the synthesis of surfactants based on biobased building blocks, such as polyglycerols. This includes synthesis, surface property characterization and the study of specific molecular interactions
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-level reasoning, and ensuring consistency between detailed simulations, experimental data, and higher-level system models. The researcher is expected to contribute to methodological advances in MBSE
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innovative group and contribute to exciting research in the Manufacturing field on Digital Twins within a collaborative and dynamic environment. About us The Department of Industrial and Materials Science
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. Demonstrated hands-on experience with circuit simulation and layout tools (e.g., Cadence, ADS, HFSS) and high-frequency measurements is highly meritorious. A strong publication record in relevant areas is
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within the last three years prior to the application deadline Experience in design and fabrication of superconducting quantum devices Hands on microwave simulation software Experience in low-noise high
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group at the Department of Physics at Chalmers University of Technology as a Postdoctoral Researcher. About us At the Division of Materials Physics , we explore the fundamental links between molecular
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motivated candidate with experience in microbiology and protein biochemistry. With us, you will experience a dynamic and supportive work environment, with opportunities to collaborate with AI experts and
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help advance knowledge in the field of variation simulation and digital twins. About us The Department of Industrial and Materials Science shares knowledge and their vision of technical solutions
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methods and models for digital twin simulation in autonomous shipping, and integrate them into a cohesive model. Energy optimization: Develop a dynamic energy optimization model for hybrid and electrified