14 agent-based-simulation-"Multiple" PhD scholarships at Chalmers University of Technology
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for a PhD position that combines research in the field of intelligent mission planning and learning-based optimization with real-world applications, in collaboration with Volvo Group. This is an ideal
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control and its integration with learning-based motion prediction under uncertainty. - Validate methods through simulation and collaboration with industrial partners (Volvo Cars and Volvo Group). - Publish
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and impacts on the marine environment. This is an opportunity for you to contribute to science-based guidance of the maritime industry in the green transition. The goal is to provide risk-based decision
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This PhD project focuses on strengthening network security for large-scale distributed AI training. As training increasingly spans multiple data centers connected over wide-area networks, it
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to investigate flow-induced forces in hydraulic turbines under varying operational conditions and how these forces affect the degradation and lifetime of the machines. About the position The position is based
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, with strong emphasis on Hydraulics and Geomechanics Genuine interest in modelling erosion processes in sensitive clay slopes and willingness to work with simulations at boundary value level to enable
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. We seek to holistically address the multiple pressures that ships pose on the marine environment and bridge the gap towards environmental management and spatial planning. Read more here https
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for Quantum Technology (WACQT, http://wacqt.se ). The core project of the centre is to build a quantum computer based on superconducting circuits. You will be part of the Quantum Computing group in the Quantum
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found in the areas of: Human-Technology Interaction Form and Function Modeling and Simulation Product Development Material Production and in the interaction between these areas. The research covers
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for validation of CFD results. Implement novel unsteady CFD and next generation in-house AI based design tools validated by the gathered experimental data on GKN resources with tight collaboration