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Are you passionate about advancing sustainable mobility solutions? Do you enjoy working at the intersection of artificial intelligence, optimization, and energy management? We invite applications
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/thesis: Industry-/collaboration PhD student in optimized off-road driving in forests Research subject: Soil science Description: We are looking for an industry/collaboration-based PhD student to develop a
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and machine learning to tackle the complexity of force allocation and motion planning under uncertainty and actuator failures. The project combines theoretical research in stochastic optimal control
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, localization, and sensing, with a focus on developing next-generation multiple-antenna systems while optimizing overall system performance. As a doctoral student, you devote most of your time to doctoral studies
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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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mathematician (doctoral student). Karlsson’s group is part of the Division of Optimization and Systems Theory within the Department of Mathematics at KTH. Currently, a large focus of the group is to develop
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principles as well as material properties of extremely thin silica membranes. In this project, you as a PhD candidate will carry out: detailed theoretical studies and optimization of light guidance in HCFs
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-fabrication processes for superconducting devices Automatic bring-up and calibration of quantum processors Design and simulation of quantum processors Optimal-control techniques for high-fidelity qubit
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extensive expertise in technology and systems for sustainable production of food and bioenergy, including optimal nutrition circuits and logistics systems. Within the field of methodologies, we have extensive
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: detailed theoretical studies and optimization of light guidance in HCFs, characterization of fabricated HCFs (on both structural and optical transmission properties), experimental investigations of material