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structured SPE data Develop ML models to predict key polymer properties relevant to battery performance Create generative models for the inverse design of novel SPE candidates within the targeted chemical
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well as the performance of active flight control systems remain underexplored. Addressing these gaps is essential for the success of this technology. This research project aims to support the development of safer, more
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high-quality research on interpretable and learning-based stochastic optimal control for over-actuated electric vehicles, with a focus on ensuring robustness and fail-safe operation. You will: - Develop
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As a PhD student you will perform research with substantial theoretical and experimental components that should be published in peer-reviewed major international journals and at major conferences
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As a PhD student you will perform research with substantial theoretical and experimental components that should be published in peer-reviewed major international journals and at major conferences
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partners over the past five years. Major responsibilities Your major responsibility as a PhD student is to perform your own research as part of the research group in CAM2 Centre at Chalmers. The position
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, testing facilities, and nano satellite platforms. As a PhD student you are expected to perform both experimental and theoretical work within your research studies as well as communicate your results
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the work is performed in close collaboration other research teams active at Uppsala University and SciLifeLab. These contribute to the project with knowledge in synthetic organic chemistry, biochemistry
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The position generally also includes teaching on Chalmers' undergraduate level or performing other duties corresponding to 20 percent of working hours Contract terms and what we offer: The PhD positions
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into two main areas: (1) material development and characterization to ensure optimal sensing and mechanical performance, and (2) structural evaluation of SS-FRCMs under environmental stressors such as freeze