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distributed WaRM experiment (for details see here: https://onlinelibrary.wiley.com/doi/10.1002/ece3.9396). The employment is fulltime for three years. The deadline for applications is March 26, 2026 and the
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on the long term globally distributed WaRM experiment (for details see here: https://onlinelibrary.wiley.com/doi/10.1002/ece3.9396 ). The employment is fulltime for three years. The deadline
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discriminant models Design and use of autoencoders (VAEs, GANs), diffusion models, and other ML methods for analysing and discovering patterns in probability distributions in latent space. We are not accepting
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environment. We value strong interpersonal skills and the ability to communicate and collaborate with others both within academia and industry. We value the qualities that an even distribution of age and gender
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for this Postdoctoral researcher position will focus on one or more of following key areas, where proof of previous work with experimentally verified results is necessary: - Distributed robotic autonomy for embodied
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techniques such as ICP-OES/ICP-MS, SEM, XRD, or particle size analysis Particle characterization techniques such as particle size distribution analysis or tap density measurements Hydrometallurgical processing
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: - Distributed robotic autonomy for embodied intelligence - Data-driven and learning-based control - Decentralized decision-making and distributed optimization - Belief-space and uncertainty-aware planning - Neuro
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: - Distributed task and motion planning - Multi-agent navigation in constrained environments - Predictive collaboration with heterogeneous teaming - Perception-aware predictive motion planning - Distributed and
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Research, SSF. Project description You will work in the RESIST project and primarily contribute to the area of protection of distributed AI. RESIST is in collaboration with Linköping University, Örebro
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for this Postdoctoral researcher position will focus on one or more of following key areas, where proof of previous work with experimentally verified results is necessary: - Distributed task and motion planning - Multi