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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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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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optimize catalysts for the production of sustainable aviation fuels from bio-based feedstocks. The use of bio-based feedstocks results in new challenges and the optimal catalysts as well as the relevant
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particular focus on the effects of boundary layer ingestion. The work also includes: Whole-aircraft noise prediction Flight trajectory optimization Environmental and societal impact assessment of future air
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the theory of optimization algorithms and high-dimensional statistics to address some of the most fundamental questions in ML such as the behavior of neural networks. The environment of this project is highly
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on designing and synthesizing advanced materials for next-generation batteries—such as solid-state, multivalent-ion, or aqueous rechargeable systems—while collaborating with the research team to optimize
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, accepted, or under review), 2) experience in optimization or machine learning. We would like to know where your interest lies. Therefore, you are required to submit a research statement where you describe
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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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on interpretable, learning-based stochastic optimal control for over-actuated electric vehicles—vehicles with more actuators than degrees of freedom, which enable sophisticated control strategies but also increase