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research consortium based at Umeå University and Karolinska Institutet. The PhD position offers you the opportunity to develop into an independent researcher who plans and performs experiments, interprets
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NEST project RAM³, which aims to enable the use of recycled aluminium in high-performance applications through machine learning, computer vision, and materials science. The focus of this position is on
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support to competent authorities on how to include shipping pressures and impacts in marine environmental management and spatial planning. Research environment Our research aims at supporting sustainable
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to include shipping pressures and impacts in marine environmental management and spatial planning. Research environment Our research aims at supporting sustainable development of the maritime shipping sector
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reimbursements for medical care. Eligibility requirements for doctoral education In order to participate in the selection for a doctoral position, you must meet the following general (A) and specific (B
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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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network on microclimate variation and its effects on roadside biodiversity Description: The doctoral student will be part of a research project funded by the Swedish Transport Administration (Trafikverket
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network. This project aims to develop skills for an autonomous mobile robot to perform complex manipulation tasks. Our goal is to enable continuous learning, allowing the robot to improve over time by
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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