10 combinatorial-optimization PhD positions at Chalmers University of Technology in Sweden
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Are you curious about harnessing the unique flavour properties of micro- and macroalgae? In this project at Chalmers University of Technology , challenges and possibilities with algae as food ingredients will be explored, maximizing the acceptance of algae-containing foods on the European...
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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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to optimally prepare it for use in AI-driven systems and solutions. About us The Department of Computer Science and Engineering at Chalmers and University of Gothenburg in Sweden with approximately 300
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urban catchments. Develop road designs that optimize water accumulation or flow. Create a framework for the selection and design of climate-adapted roads. The research will primarily involve hydrological
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evaluation frameworks and/or the development of energy system optimization models. The research is applied and closely linked to industrial interests and needs. About the research Our research aims to provide
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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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on building the next generation of quantum processors based on superconducting circuits. To achieve this ambitiuous goal, we have a variety of projects related to: Development and optimization of nano
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of the PhD student will touch upon various topics multi-body dynamics, optimal control theory, machine learning and robotics and artificial intelligence in general. The focus is broadly upon the development
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superconducting circuits. This project focuses on modeling the quantum dynamics of these circuits at the Hamiltonian level and optimizing their control. You will develop theoretical models and optimization
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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