39 optimization-nonlinear-functions PhD positions at Chalmers University of Technology in Sweden
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artificial intelligence), exploring future skills, and optimizing equipment management. You will work in close collaboration with major industry partners to collect and analyze real-world empirical data using
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to the affected service layer, resulting in suboptimal remediation. This project introduces a bottom-up approach to network security, integrating physical-layer perspectives into the design and optimization
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.” In this role, you will develop advanced methods to estimate rail roughness and defects based on onboard vibration and sound signals—contributing to a quieter, more reliable, and cost-efficient railway
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PhD Position in Theoretical Machine Learning – Understanding Transformers through Information Theory
Join us for a fully funded PhD position in theoretical machine learning to uncover how and why transformers work. Explore their inner mechanisms using information theory. As part of this project
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and development. Project overview The ongoing transition from synchronous machine-based generation to converter-dominated renewable energy sources presents new challenges for the operation, control, and
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at the Division of Fluid Dynamics, within the Department of Mechanics and Maritime Sciences at Chalmers. The project is carried out in collaboration with Vattenfall Research and Development, and is part of
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The main purpose of this project is to develop new biobased surfactants using sustainable raw materials as an alternative to conventional petrochemical-derived surfactants. Since most surfactants
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the demand for energy storage soars, lithium-ion batteries lead the charge—but are they truly the most sustainable option? We are diving deep into the environmental performance of emerging battery
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able to understand and quantify the triggers and precursors for shallow slides in sensitive clays as a function of time (>100 years). Information about the division and the department Geotechnics
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Chalmers' new research initiative Ocean is seeking a highly motivated PhD student in environmental analytical chemistry and machine learning. In this role, you will work with high-frequency